﻿{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.1 合并数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1460, 81)\n",
      "(1459, 80)\n",
      "(2919, 79)\n",
      "                Id   MSSubClass  LotFrontage        LotArea  OverallQual  \\\n",
      "count  1460.000000  1460.000000  1201.000000    1460.000000  1460.000000   \n",
      "mean    730.500000    56.897260    70.049958   10516.828082     6.099315   \n",
      "std     421.610009    42.300571    24.284752    9981.264932     1.382997   \n",
      "min       1.000000    20.000000    21.000000    1300.000000     1.000000   \n",
      "25%     365.750000    20.000000    59.000000    7553.500000     5.000000   \n",
      "50%     730.500000    50.000000    69.000000    9478.500000     6.000000   \n",
      "75%    1095.250000    70.000000    80.000000   11601.500000     7.000000   \n",
      "max    1460.000000   190.000000   313.000000  215245.000000    10.000000   \n",
      "\n",
      "       OverallCond    YearBuilt  YearRemodAdd   MasVnrArea   BsmtFinSF1  \\\n",
      "count  1460.000000  1460.000000   1460.000000  1452.000000  1460.000000   \n",
      "mean      5.575342  1971.267808   1984.865753   103.685262   443.639726   \n",
      "std       1.112799    30.202904     20.645407   181.066207   456.098091   \n",
      "min       1.000000  1872.000000   1950.000000     0.000000     0.000000   \n",
      "25%       5.000000  1954.000000   1967.000000     0.000000     0.000000   \n",
      "50%       5.000000  1973.000000   1994.000000     0.000000   383.500000   \n",
      "75%       6.000000  2000.000000   2004.000000   166.000000   712.250000   \n",
      "max       9.000000  2010.000000   2010.000000  1600.000000  5644.000000   \n",
      "\n",
      "           ...         WoodDeckSF  OpenPorchSF  EnclosedPorch    3SsnPorch  \\\n",
      "count      ...        1460.000000  1460.000000    1460.000000  1460.000000   \n",
      "mean       ...          94.244521    46.660274      21.954110     3.409589   \n",
      "std        ...         125.338794    66.256028      61.119149    29.317331   \n",
      "min        ...           0.000000     0.000000       0.000000     0.000000   \n",
      "25%        ...           0.000000     0.000000       0.000000     0.000000   \n",
      "50%        ...           0.000000    25.000000       0.000000     0.000000   \n",
      "75%        ...         168.000000    68.000000       0.000000     0.000000   \n",
      "max        ...         857.000000   547.000000     552.000000   508.000000   \n",
      "\n",
      "       ScreenPorch     PoolArea       MiscVal       MoSold       YrSold  \\\n",
      "count  1460.000000  1460.000000   1460.000000  1460.000000  1460.000000   \n",
      "mean     15.060959     2.758904     43.489041     6.321918  2007.815753   \n",
      "std      55.757415    40.177307    496.123024     2.703626     1.328095   \n",
      "min       0.000000     0.000000      0.000000     1.000000  2006.000000   \n",
      "25%       0.000000     0.000000      0.000000     5.000000  2007.000000   \n",
      "50%       0.000000     0.000000      0.000000     6.000000  2008.000000   \n",
      "75%       0.000000     0.000000      0.000000     8.000000  2009.000000   \n",
      "max     480.000000   738.000000  15500.000000    12.000000  2010.000000   \n",
      "\n",
      "           SalePrice  \n",
      "count    1460.000000  \n",
      "mean   180921.195890  \n",
      "std     79442.502883  \n",
      "min     34900.000000  \n",
      "25%    129975.000000  \n",
      "50%    163000.000000  \n",
      "75%    214000.000000  \n",
      "max    755000.000000  \n",
      "\n",
      "[8 rows x 38 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "train = pd.read_csv(\"./origina_data/train.csv\")\n",
    "print(train.shape)\n",
    "test = pd.read_csv(\"./origina_data/test.csv\")\n",
    "print(test.shape)\n",
    "alldata = pd.concat((train.loc[:,'MSSubClass':'SaleCondition'], test.loc[:,'MSSubClass':'SaleCondition']), ignore_index=True)\n",
    "print(alldata.shape)\n",
    "print(train.describe())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.2 pd.describe() 查看数据情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "explore = train.describe(include = 'all').T\n",
    "explore['null'] = len(train) - explore['count']\n",
    "explore.insert(0,'dtype',train.dtypes)\n",
    "explore.T.to_csv('./origina_data/explore1.csv')\n",
    "\n",
    "explore = alldata.describe(include = 'all').T\n",
    "explore['null'] = len(alldata) - explore['count']\n",
    "explore.insert(0,'dtype',alldata.dtypes)\n",
    "explore.T.to_csv('./origina_data/explore2.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.3 计算各特征对应缺失值占比，返回前20的情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total</th>\n",
       "      <th>Percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PoolQC</th>\n",
       "      <td>1453</td>\n",
       "      <td>0.995205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MiscFeature</th>\n",
       "      <td>1406</td>\n",
       "      <td>0.963014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alley</th>\n",
       "      <td>1369</td>\n",
       "      <td>0.937671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fence</th>\n",
       "      <td>1179</td>\n",
       "      <td>0.807534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FireplaceQu</th>\n",
       "      <td>690</td>\n",
       "      <td>0.472603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LotFrontage</th>\n",
       "      <td>259</td>\n",
       "      <td>0.177397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageCond</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageType</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageFinish</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageQual</th>\n",
       "      <td>81</td>\n",
       "      <td>0.055479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtExposure</th>\n",
       "      <td>38</td>\n",
       "      <td>0.026027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <td>38</td>\n",
       "      <td>0.026027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <td>37</td>\n",
       "      <td>0.025342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtCond</th>\n",
       "      <td>37</td>\n",
       "      <td>0.025342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtQual</th>\n",
       "      <td>37</td>\n",
       "      <td>0.025342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MasVnrArea</th>\n",
       "      <td>8</td>\n",
       "      <td>0.005479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MasVnrType</th>\n",
       "      <td>8</td>\n",
       "      <td>0.005479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Electrical</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utilities</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Total   Percent\n",
       "PoolQC         1453  0.995205\n",
       "MiscFeature    1406  0.963014\n",
       "Alley          1369  0.937671\n",
       "Fence          1179  0.807534\n",
       "FireplaceQu     690  0.472603\n",
       "LotFrontage     259  0.177397\n",
       "GarageCond       81  0.055479\n",
       "GarageType       81  0.055479\n",
       "GarageYrBlt      81  0.055479\n",
       "GarageFinish     81  0.055479\n",
       "GarageQual       81  0.055479\n",
       "BsmtExposure     38  0.026027\n",
       "BsmtFinType2     38  0.026027\n",
       "BsmtFinType1     37  0.025342\n",
       "BsmtCond         37  0.025342\n",
       "BsmtQual         37  0.025342\n",
       "MasVnrArea        8  0.005479\n",
       "MasVnrType        8  0.005479\n",
       "Electrical        1  0.000685\n",
       "Utilities         0  0.000000"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total = train.isnull().sum().sort_values(ascending=False)\n",
    "percent = (train.isnull().sum()/train.isnull().count()).sort_values(ascending=False)\n",
    "missing_data = pd.concat([total, percent], axis=1, keys=['Total', 'Percent'])\n",
    "missing_data.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.4 查看corr()相关矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['SalePrice', 'OverallQual', 'GrLivArea', 'GarageCars', 'GarageArea',\n",
      "       'TotalBsmtSF', '1stFlrSF', 'FullBath', 'TotRmsAbvGrd', 'YearBuilt'],\n",
      "      dtype='object')\n"
     ]
    },
    {
     "data": {
      "image/png": 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T2P6XItHRmeHsZKejCeUO+cYA8939GTObC+yfzCM3ipAtzrb5rZnllllUJMuzcgfbPYDJSa3yEuBVwkF7rX0RmA/s18LtG9LyYBkAd28ws4lmdj+hPnoG4ecBTWsnIiIi0sk6ejD8DGGgejihbOA/zKwvcBBwT7LoesIcc+8Ad+TMMjEXOMPd78yJNf470AbInVn714SB8qbu/knS/vUCtvVPwNlm9nV3fyiJOxh4DagmHOX4naRtA2GAnTU0Z9u2J9TI7JitETazUwj1wyIiIiJtr+vVDHdZHToYdvc6MzscuMfM6oCrCCULnyPMVbcaOC9pfhNwFrAd8M2c1dwA/K+ZvUTILu9HmJZtD+CpJrodTBi81if1u8cRZrH4Wyvb+noym8QtZnYSoe53Q8LsEquBP7v7X7LNgZ+a2WhCCcRpef03kEz5YWZfINQwp54cWkRERKRFRVTG0N46/Kf6JMv6JcLkyK8RJly+g5A13j57EJy7LwQeBZa4+/M5q7iIcB7rB5PYycCh7t7UQBhCBroP4YwlswlnLLmVcGrA1rb1bOAowkF6cwhzI78FPADsYGbHJE2vIRyU9wphzrxHCANgkv//ADxlZksJWeIrgOFm9p8MsoiIiIh0vE456Ya7vwIcWEC7po46rCeUPvy6mZiyvOvvA7u20MdhOf9PauL2PxFKJtZiZpsQstYkA/hv5zXJnanilOSS68Lk7zTC1CAiIiIibUNlEgUry2QyrbeSLuXyjQ+JftAWlMe/KGJH6IMa439omNejPjrmghfOj47ZzPaPjplcuVV0zFO9mp26ulkbZHpFx2zUEPfoPN+zuvVGeVanOHtRVVl89c/2DVWtN8qT5i1+Vnn8/vRK8T11h+q4l+dNlfEn3bSyfq03yrN+Q/zrc2Z5/OuzT4ofHPtm4mPuqMmfi791m1UOi2rfryw+X/TZxvwzzrZudVn85/DYuvjn5icpivN6p3ixLUnRz4jIp9pHKVJ5A1Lsyzs9053F7cJZt3d6kmvNI39o9wFe768e2+n72RY6JTMsIiIiIu1INcMF0/ReIiIiIlKylBkWERERKTaqGS6YMsMiIiIiUrKUGRYREREpNsoMF0yZYREREREpWcoMi4iIiBQbzSZRMGWGRURERKRkKTMsIiIiUmxUM1wwZYZFREREpGQpMywiIiJSbFQzXDBlhkVERESkZCkz3A2tSfEVZqOG+KDRtQ1R7d/vFd0Fk0/oHx2zme0fHfO2/zk6pu7O30XH7Hrzm9ExK5ZURcfcXjc4qv1315RH97HtTouiY5a9Wxkdc9/y+P1/tmxldMzP6sqiYxoy8TGPVPaOan/jvvXRfXzw4PLomJsYEB0zP1MdHfOt2r7RMQMb66JjTn7y19Ex9ff8Map94+L4+3nmX2qjY1bXVkTHfKf6neiY0/tuHR0zsyITHTO4Mf51E9vPoBR9LI1/G+TsQ+P3v8tQzXDBlBnuZGZWbmajO3s7REREREpRt8sMm9klwPeBrdx9fs7yXsBzwHvu/p027vNDYChQD5Qlf/8FnOjuraYCzWwT4DVgM6AP8A6wsbt/CNwFvAxMbsttFhERkRKmmuGCdcfM8C+A2cANect/BQwAjminfo9w937u3hcYAbwH/NXMWv2txt3fT2LnNXHziLbeUBEREREpTLfLDLt7rZkdBLxkZse5+5VmtjtwHLCTu39iZhsCvwO+DNQBdwL/6+7VyeD1NOBgYCQhy/tX4Jhk3VOBSmBrYGDyN38bqs3sSuAoYBCw1MyeAR5y98kAZjYReMzde5rZOJJscO56zGwKsCPweTPb0t2/24Z3lYiIiJQq1QwXrDtmhnH3d4BjgAvNbBtClvgkd3/FzMqB+4DVwKbA/wDbAhcn4QcBxwLfcPdBwC7AAcnyrD2AvQFz9wX5/ZtZP+BoYJq7L12H/TiMUNpxngbCIiIiIh2v22WGs9x9qpl9BXgW+JO7X5vctAPwWWBnd18NrDSz04GnzOwk4H7gKXefa2ZDgPWAjwlZ4qxnkwF3rmvM7ApCzXB/oBZo09pkERERkTahzHDBumVmOMe5QG/g7JxlY4AKYJ6ZLTOzZcBDQCMwCigHzjezRcA/gJ8AvVj7vvhUNhg4yt0HuftAoAr4MXCPme3VtrskIiIiso4ymfa/FIlumxlONOT9BZgLrADWc/dGADPrS6jXnQVcDWwEbOLuK5LbZ+Stt8VH2N1rgVvM7GfA14EHkm3IvT+HptgfEREREelA3X0w3JTngHnAb8xsEiHjezWwHaF8YjBQDdSbWW9CZnhzQja5IGbWA9gLGA+clyx2YD8zu5yQfT6hwNXVEA7UExEREWkbKpMoWHcvk/iUJGu7FzAOmAnMIUy5tleSKf5lcn1hcvt2wO3Alq2s+jozW2lmK4DlwG+A4939nuT2XwGLk3U+layzELcAR5nZQwW2FxEREZE20q0zw+4+i3BAW/7ymYQZIpqKeZcwg0Rz6zykiWUjm2qb12Y28JW8xVfl9Jm7nWU5cVOAKa2tX0RERKRgygwXrFsPhktVQ+tNPiXF6eVZ3SPuh4P16zMs6Bl3vvhMTW1Ue4DJlVtFx9Td+bvomIoDT46OmX3ez6NjlmfiX4Z1veMe0Md6l7NvTU1UzCcze0W1B1i9Kj5mi5r66JiFvftExwwduig6ZvpH8aX/VZ/+ft6iq+5bj6P3+CgqZtnqAVHtAfr2iv8hsKqsPDpm47I10TELyqqiYxpfeCQ6pv6/Jy0tPGZJ3POztn5wdB99etVFx2xfMTY6piLFh0fPDjpGqjLydbOmB/SJHOsNTLH/mbr4x0a6Hw2Gpc3EDoSl48QOhKXjxA6EpePEDoSl48QOhEuSTsdcsKKrGRYRERERKZQywyIiIiLFRjXDBVNmWERERERKljLDIiIiIsWmiM4Q196UGRYRERGRkqXMsIiIiEixUc1wwZQZFhEREZGSpcywiIiISLFRZrhgygyLiIiISMlSZlhERESk2OgMdAVTZlhERERESpYyw93QmrL4uQPrysqiY0aVrYlqX15XFd1H3Wtzo2Oe6jU0OmbXm9+Mjpl93s+jY7affmF0zMydj42OeXLN4Kj2izKV0X1sNqI2Oqb34PiYpTPinzeN9IqOGbhJ/LatXhifL+gXmYxZ9Hx8HxU94jM+n61JMedoZfxjM2zIouiYAdXV0TGzz305Ombo2Pqo9mUpPiFX1lVEx6yq6x0ds37v+OfAmviPAcbUxwctT5FmWx35uVad4jOtOsX+Z9bEv290FZlGzTNcKGWGRURERKRkKTMsIiIiUmw0m0TB2n0wbGbZPP04d38v77bfAicDh7v7lHXo4xFgqbsf2MRtpwE/AMa7e6rfDMysEvgAWAF8xt31DBMREZGuSwfQFayjyiQWA4fkLjCznsD3gJVtsP4rgG+a2VrFpGZWBvwYuCLtQDhxIPAGUA/svw7rEREREZEupKPKJG4Hvg+ck7NsT+AtYOPsAjPbAPg9sD0wApgLnOPuU5PbjwJ+DgwBZgO/dfebgfuTtocCv8vp42vAUOCmJD4DnAgcD6wPvAIc4+5vmNlE4BbgH8DXgbPc/bJkPccl6+gLnALcm7PNk4Cdkm0ak8Q6cAGwL1ABPASc5O5Lk5jDgJ8k7XsCTwBHuPvHBd2bIiIiIi3RAXQF66jM8P3AIDPbKWfZ4cANee2uA1YD44H+wFXANWbWz8w2Aa4EvuHugwiD4ivMbGBStnAV8KO89R0N3Ojuudnng4BdgY2ANYRBa9ZI4GVgWHbbzGxCsj1TgeuBrc1sx7x+diMMsscCLwI3ApsA2wKfIdzPtyfr+zwhk32Uuw8BtkzWf2KT95yIiIiItJuOGgzXAncQMrck5Qw7k5NhTRxFyJjWEAamK4A+wHpAA9AIHGFmXwAeAwa5+/Ik9npgbHbAbWYbAXsRBtC5LnX3+e6+ArgH2CLv9pvdvS5nAH08cJO7f+LuS4BbCXXOud5z92fc/RNCJvoA4AR3X5Qs+ynwNTPbFJgObOnuL5jZAEKGelGyvyIiIiLrrrGx/S9FoiOnVrsJ+E5yMNrBwJ/cfXVem7HAI4TB4d2EDC5AD3efTcjAbpq0+Ri4xMyqAJKB6m3AEUnMj4HH3P2dvD4+yvm/DijPu31B9h8zG0KoFz7EzBaY2QLgO8D+Zja2qRhC6QPA82a2zMyWAe8C1YRscQNwopnNJ5RpnAkMQNPciYiIiHS4DhuAufu/CYPGfQizO9yYe7uZVRDKKW4Dhrr79sAlObcPS9bzDUKm+JuEkofc0ojLCQPugcnyy4iUd6DdEcDrwObANsllc+AF1i5ryI3JnkXC3H1QUtIxBPg88CRwEqGueBt338Td9yPUP4uIiIi0DWWGC9bR2cibgElAlbv/M++2SkJJxCp3z5jZKCB7Oq8KwoF2j5rZbu5eD8xJblucXYG7v0qo+b2MUA/8cNoNNbMe/LfmeEHuBfgj8CMzG5Qf5+5zCZnrS8xssJn1As4DngJ6A4MJZSO1ZtbTzA4hDI7jT1skIiIiIuukowfDUwkHi+UfOEdSo3s4cJaZrSDMsJAtmdjS3V8izOpwtZmtJAwurwDuylvV5YTa5HWdTm0fYEPgziZuu4OQDT6ymdiDCYPx6cn27wTskdQ3X0SYs3g2MI8w5dxVhAPpRERERNZdJtP+lyLR7lOruXtZzv9zyavRdfdxOf9PJQyYc12Qc/sNNDGQzlvfXXx6gPypbUmuTwGmJP9PA3K39W+EbHVT61lFqPNtbhsW8+mZLbK3LSFMuSYiIiIinUynY+6GBjSWtd4ozwfl8bU9O/esi2o/tqEhuo8Pn+8bHbNBpld0zIolVdExyzPxL4+ZOx8bHTP26T9Ex1ROODOq/beWTIvuY/kOO0fHNMxfEh1z08zoEEbEhzDrhU9VNbXqGxdvEh1z76lxO/T00mHRfSzNP+y3ADMr4l7PAFUpfjx8fOnw6Jhd+sVPsT53af/omOq34l7Tg4fkH+Pdun4p7ufl9fFVcuXEfw501E/BVlsfHfNGZdxjUxO/+/RNUeJaN/OT+KCuoohqetubZjAQERERkZKlzLCIiIhIsdEZ6AqmzLCIiIiIlCxlhkVERESKTUY1w4VSZlhERERESpYywyIiIiLFRjXDBVNmWERERERKljLDIiIiIkUmo3mGC6bMsIiIiIiULGWGRURERIqNaoYLpsGwiIiISLHR1GoFU5mEiIiIiJQsZYalWS/UDoxqv15D/LfQf6f4Oja6oSw65va6wdExdb3jf2J6ck18P5UTzoyOOfOF86Lav7rdCdF9PHpt/INTXzYsOqZvZUN0zPoN8dv2RFn/6JhlJ3t0DOW9opq/WRG///0z8fu/YaYiOqaW+NfAgvL4mGdWDomOeaN3fXTMoEzcc6DXxwOi+xiZIhm3KO4pA8D4+vjnwOIUj82w+LuZ2RXtP7RIk8mLfwXAda9snCIKfp4qqo2pTKJgygyLiIiISMkqysGwmW3S2dsgIiIi0mkaG9v/UiQ6pEzCzDJANdAAlAG1wJPA8e7+YRv3tQ3wPFCZXD8MuAFY3UTznYF+wIPu3q/A9X8RmAR8HigHZgM3Ar9z90zSJnd/c13j7qeY2frAJcDuyTqeAU5y95kF76iIiIiIrLOOrBne092nAZhZf+BmYCowsY37GQTkV2DNcfcxLcQUOhAeCzwGHAnsDdQD2wP3Ar2ByTnN/7O/TZgKLATGEQbMlwJ/A7YqZDtEREREWqSa4YJ1ygF07r7CzK4F7skuM7P9CYPJkcA84EZ3vzC5LUMYgP4C2BB4CPgVcAVhAPkm8D2gEXgwiVlJyPy2yMwmAn9397Lk/ynA9cAxhOzyY8AR7r6CkA2uBe5y99pkFf80s58CYwvZdzOrIGSNz3b3T5JllwGvmtlgd19ayHpEREREZN11ymDYzIYAhwN/Sq73Bm4D9nf3h5JSh6fN7K/unj2c+wjCYLSKMPidAHwF+BB4GPilu//IzPYkDG77JeveOnLzRgMbAJsC6xNKGI4CLgamEcotXjCzu4HngOfd/a5CV+7udcA+eYsPAN7XQFhERETahOYZLlhHDobvN7N6wkF7/YHlwF45t1cDB5tZDfAsMNDdcx8ZHajBAAAgAElEQVTJi7KDRTObDryYHSib2RPAl1roe5SZLctbNtndL26m/TnuvgaYaWbTgC0A3H2hmX0OODbZ9jOAHmb2MKHm950m9jfrfXffLr8jM/shYRaWfVvYfhERERFpBx05GN4np2a4N6EMYZqZfcHdXzKznQmDy7uBPsA9ZnZiTrb045x1NQC5g9tGWp4Zo7Wa4bW4+0c5V+sIB7llb1sEnAOck+zHjsDZwCNmNs7dswfN/Wd/m2JmPYGLgB8A+7r744Vun4iIiEiLuljNsJmNAK4DdgHWAFe5+znNtH0Z2Jy1JyL4vLvPMLN+wB/476/stwE/TX55T6VTplZz9zXu/jtgBbCHmQ0ARrj7QcAwwh31eeD0nLBOf1TN7BYzuzF7PdmPJ4DjgTFAQWdcMLOBhFrkrwA7aCAsIiIiRe4OYDGhBHV34Idm9t38RmZWCWwJbOPu/XIuM5ImVwDDCcdqbQ18EfjZumxYZ9UM9wS+T5j54RlCJvgBMzscuB2YQ8j2Lk6x+pqkj4Huvrxttvg/bgP+YmavEaZTW04YBP8v8JS7t7q9ZlYG/IXwReQL7r6yjbdRRERESlymC80DbGbjCLOHrZ+Uob5hZr8HjiOM+3JtQ8gcv93EenoD3wV2ScZ4y83sXOBy4Ndpt68jB8MPmlkDIcObIezkQe7+LICZfZswm8Q1hDvhDsJcvLFeI9QczzOzb7TFhme5+4Nmtg+hxvcMwnRqiwkHAh5d4Gp2JjwhaoAFZpZ723h3n9NmGywiIiLSTsxsECGxmW+Zu+eWs24JfJxXhjoD+FwTsROAlcATZrYVMItwLNd9wGaE6XPfyFvPRma2nrsvSbMfHTIYdveyAtrcB9xXSLy7T8y7Pinn/1WElHmuKS30O41wIpC1/s+5/bC8648Cjza3vqa2N++2p/L7EBEREWlTHVMzfBLhuKl85xBOUJbVn0+f/Gw1oTIgXxnwb8J0ujMJM27dnUx/2zMnlrz/+wBddzAsnW8Rta03yrNrfdzT443K+KfTUcPmR8ecs6ig0uy1fHdNeeuN8vTuUd96ozyLMpXRMd9aMi065tXtTohqf89Ll0X3serEI+Jj3o8O4YO5G0bHVMR3w5d75k8oU0DM8ndab5TnkMHbRrU/YeDHrTfKc8uy4dExO9XURMe8WRH/fN61Kv6z6J+r14uO+U5t/HtaZc/8k4K2bE1d/HvasxW9o2PG18S/18xI8X47sDE+DzMz/xRWBahJcYhPz8gc0XpxDyUAH5XHb9e+GVUytuL3NJ1wzH/DXUX4NT1XH+CT/EB3v4JQF5x1h5kdAnwbuDVZ1jtZZ3Y9NLWuQmkwLCIiIlJsOiAznJRCFJJpmA4MNbOhOcdXjWftcgcAzOw4YKa7P5CzuIr/1hHXEWaaeDFnPR9mT2SWRqfMJiEiIiIipSE5D8OzwMVm1tfMxgMn0nRWeUPgCjP7jJn1TCZX2Am4KSmFvRs438zWM7ORwJnNrKdgygyLiIiIFJuudwa6bwNXEmYMqwWudPfrzWwU4czCe7r704Ra457A3wlT1r4J7OXu7ybrOYZQnjGDcB6I2wg1yqlpMCwiIiIi7crd5xMOhstfPgfol3O9jnDw3C+aWc8nwA/bcts0GBYREREpNl3sDHRdmQbDIiIiIkUmo8FwwXQAnYiIiIiULGWGRURERIqNMsMFU2ZYREREREqWMsMiIiIixaaxy02t1mUpMywiIiIiJUuZYREREZFio5rhgmkw3A01lsXHfNCwKjpm+51WR7UfO6NPdB/r7bdBdMzqP8bvy7Y7LYqO+WRmr+iYzUbURscs32Hn6JhHr437UWfViUdE99H30uuiY3ovmh0d86+vXxodM76sb3TM6K/WR8e89OLI6Ji7Pop7W63sG79d9cujQ3ivvDI6ZnZ5/M+sVX3qomP22ujD6JiG2vg3wr5WHtW+fEj886z/vfEPTs8BDdExj9YNiI7ZvD7+I390bfyAql+Kn+dfr4p7bFI8/FQRH7T5WZvGdyTdjgbDIiIiIsVGmeGCdbmaYTOrMrMNO3s7CmFmm3T2NoiIiIhIem2eGTazq4FDctbfC8j9vX18ch7q5vwDuASYWkBfk4EvuPseZrYH8CiQ/Q29DFgO3AWcmpzrus2Y2U+AbwBfSa73AH4O/ADYGKgFngcmufvzSZsjgGtZ+/7I2tHdX2/LbRQREZHSlMkoM1yoNh8Mu/vRwNEAZnYIMNndx0SsYsQ6dN/g7v2yV8xsHPAwsBiYvA7rbcoIWKsA6QzgO8AB7j7DzPoCJwB/N7Mt3X1m0u59dx/XxtsiIiIiIil0eM2wmfUBzgMOBHoTsqcnu/tbZvYEsCFwnZlt5e6/MLMfAccBY4By4DHgCHdf2lpf7v6umf0F+HxO/+cAPwL6AO8AZ7n7w0lm+QrgFsIgthfwO+BN4ALC4PdBQtb7+4QscA8z+9DdRwJfAqa5+4yk71XAr5OSjxFAdjAsIiIi0r5UM1ywzjiA7lpgM2AnYCEwCXjUzMa7+25m9iFwmrtPNbMdCSUTE939JTPbGPg78BPg3NY6MrPxwF7Ab5LrXyFkrbcD5gHHAFea2WeyIYSB60bAnsDfCAPg/wGGAi8C33L3681sLEmJRhJ7O/BHM1sfeIQwyH/d3X+S8n4SERERkXbWoQfQJVnhA4HT3X2Ou1cDpxMyvns2EfIKsFUyEB4ArA8sApqb76jczJYll9XAG4T63IeT22uAQcDhwFbA1cBn3D3369NZ7l5PGNAC/MHdl7v7e4Qs8dimOnb3G4GJwIpkn14BFprZuWZrzeczNmcbs5eTmtkfERERkXiNmfa/FImOzgwPSfqclV3g7o1mNgcY1UT7RuCnZnYgYVD7OtCP5gfxDe4+KHvFzIYDlwHPJZnnp5J1HQ/8L+EAu8vN7Pxsf+6+LLuu5G/2enZ7mv0C4e7PAM8kfW8A7AtcCNTz30z2TNUMi4iIiHQNHT0YngfUEbKr7wIkWdPRwIIm2p8C7A5s7e4Lk/YPFtqZuy80swuAl4AtzGwx8EEy+0QV8HXgTuAFwuA31dccMxuU7NtXkwEx7j4fuNbMtiSUZYiIiIh0iEwRZW7bW4eWSbh7A3Az8CszG5UMSH9FGJQ/kDSrAQYm/w8mTFFWa2Y9zexQYA+gopD+ktKKY4GPAAd2AB5MDs6rBuYSZoRYnGJ3/rOdSTb5fsLgd1czK0/mS54IfBu4N8X6RURERKSddcYBdCcRpjn7B2Ew+Tywm7svSW6/AbjQzD5HKGUYD8wBqgkZ3GuALzSz7nIzW5n8nyGUJzxHyNiuAu42MwPuN7OhwHzgWHd/MZlNIsbfgKPMbCmwAWGGiV8AVxIy3WWEGuNT3f22yHWLiIiIpKfMcMHadTDs7lPJO3mGu68kDIibPGjM3X9FyBZn7d3C+s/I+f8xaP3E4+4+mSbmHE7ie+Zcr89fn7t/Kef/V/n0gXzn0sIsF+5+HXBda9soIiIiIh2jMzLDso4qU3zZq880tN4oT8WI3lHtq2bHn+SvcfHy6JiqssromGXvxsesXtUrOqb34NromIb5S1pvlKe+bFhU+1XvR3dB70Wzo2N6DBsdHVOd4rlZWdbq995PKR/X3CQ0zVvx6PzomNjas8ohjdF9LJoX/1r7Qn18VVxFJv4jYvD4+uiYAvIYn/LBP/u13ihPvy2qo2NilZXFv0GvqS6o8m8tVeXxj2eaz440tZTlKQ6/iY2Iv8dgTYqYbl13G//WUrI0GBYREREpMt16IN/BOvQAOhERERGRrkSZYREREZFio8xwwZQZFhEREZGSpcywiIiISLHRAXQFU2ZYREREREqWMsMiIiIiRUazSRROmWERERERKVnKDIuIiIgUG9UMF0yZYREREREpWcoMi4iIiBQZ1QwXTplhERERESlZygx3Q2nKgKZs0BAdc//fhkW1ry4ri+5jt6cWRMds3zAwOua+5VXRMVvU1EfHLJ0R389NM6ND6FsZ93h+MHfD6D7+9fVLo2OqM/HPs7teiu/n9q3Pio4p22zz6JjJ9R9Hx2wV+TLoOSj+bfi3p28UHdM4c050zD03x29b5e7bRse8dtas6Jh36BMds+KBXlHtVzZWRPexvEd5dMymPVdGx2xRF5/LmpviE39oQ/z7en1Z/H3QL/KDrSxF0rOO+KClN74a3xHQ58hUYW1LNcMFU2ZYREREREpWt8sMm9nngYuBrYFVwL3Aae6+OnI9Y4CZwFh3n2Vm04CdgNq8pm+6+/ZmNgXA3Q9rZn09gJ8BhwGjgDrgeeAcd38uaXMYcAPQ1Lbu7O4vx+yDiIiISFMyygwXrFsNhs1sIPAgMBnYHVgf+DNwAfCTNujifHeflDL2NOD7wLeAGUBv4HjgCTPbyt3fTdrNcfcx67qhIiIiIrLuutVgGBgDPO3uv0+uf2hmtwA/MrNJwGeBGmAfYDlwk7ufCWBm/YErgG8CK4Gr025E0tdOwJBkm74OfAl40t3fTJqtBi40s42AEcC7n16TiIiISDtQZrhg3Wow7O6vAvtnr5tZWXL9hWTRAYQyhUOBPYAHzeyv7v4CcCUwFhhHeIrcvo6bsxswEXiNMLi+A7jBzIYBjxBKJF539xPXsR8RERERaSfdajCcy8x6AlcBmwIHA0cC7u43J00eNrP5wBZm9jrwHWAfd1+UxJ8KvJK32tPM7KS8ZePdfV4Tm/Ceuz+Tc/1mM3sXOIJQMjEGWGJmVwNnu3t2aoJRZrYsb12T3f3iwvZcREREpGWqGS5ctxwMm9lwQmZ3OOHAs3lmBvBRXtM6oJxQzlAJfJBz23tNrPo3ETXDn5oTzN2fBZ5NtnEDQrnGhUADkJ0LSjXDIiIiIl1EtxsMm9lWwAOEMoT93L2QCRoXA9WEMglPlo1cx035z4SFZtaPMBDf292nAbj7fOCPZrY5sN069iUiIiJSOGWGC9atBsNmNgJ4FLjN3U8uNM7da83sZuA8M3uNMCXbhW21Xe6+0sz+ClxtZscATwEVwA6E8oz4MwSIiIiISLvrVoNh4CjCzAxHmVnu+V1mA3e3Ensi8DvgDUL5xKXAvm24bYcDpwKXAaMJJzSZAfzS3ae2YT8iIiIiLVLNcOG61WDY3c8Fzo1oPybn/2rg2OSS9auc2ye2sq7Dcv6f1MTtNYT5jye3sI4pwJSWt1pERERk3WgwXLiyTCbFCb6lU00afXD0g7ZxmvPLR0fA6sgTfK9OcYL5wY3x+/Jkj0JKy9c2rqxPdEya954050RfvyE+qiKy/aIe8Y9NJfGPzfopnmjffbXg78T/8fiWp0fH/LOqPDqmXyb+PoiNqE7xutmyJj5mdq/459lnauIf0Fer4vMy9cTvz5KyhuiYqshX6IBM/H3WP8Ubx4AUMYvin870TjFE6NdB21Yb+cJpTPGc6ZHiPQ3gl7OnpgtsQwt337XdB3jDH3+y0/ezLXSrzLB0bbEDYek4sQNh6ThF8UlSpGIHwtJxYgfCpUiZ4cLplS4iIiIiJUuZYREREZFik6Jkq1QpMywiIiIiJUuZYREREZEio5rhwikzLCIiIiIlS5lhERERkSKTSTENaalSZlhERERESpYywyIiIiJFRjXDhVNmWERERERKljLDIiIiIkUmo3mGC6bMsIiIiIiULGWGu6HBKb7tVaWoHdrrix9GtV80vSq6j5HHj4uOmXTRx9ExP6uLv8+GDl0UHTNwk9romFkvDIqOeaKsf1T7L/dcFt3H6K/WR8eUjxsZHVO22ebRMY9veXp0zO5vnB8dM3ubs6JjlpbHtT/x3Pj7rOaRf0XHVGw6PDrm4WujQ9j9yWOiY3a+7DfRMbMejP/4GrN3Q3RMrA8fjo8ZNGJNdMxdczaKjqnMRIewfl38h8cw4t8HF5XHfX6sH//2xIcpRjwnX719fFAXoZrhwikzLCIiIiIlS5lhERERkSKjeYYL1y0Gw2Y2Cvgl8HVgOFAD/BO42N2faCZmCoC7H9bM+t4Exrv7nAK34TLgJ8CX3X1a9E6IiIiISJfT5cskzOyzwGtAJbAnMAAYB9wG/NXMvhK7Tnef4+79IgbC/YBDgT8Cp8T2JyIiItKRMpn2vxSL7pAZvgZ41N1/mLNsCTDVzOqB3mZ2GHA8sAyYABze0grNbAwwExgLnAdk3P3QnNsfAl5y9+xROt8H3gYmATPNzNzd89Z1KfAD4Dp3P9XMDiZkszcG3gJ+5u5PJzGbAxcDnwOGAe8Ap7p7ikMvRERERCStLp0ZNrORwE7A1U3d7u53uPvfkqv/A1wHrA88GNHNdcABZtY36XMDYHfghpw2xwFXufs84M/AT5tYT09CCcdkM9sXuBI4BlgPuAB4wMzGJm3vBV4BNgUGAo8Tss4iIiIi6yzTWNbul2LR1TPD2TmHPsguMLPdCYNJgHJgHvBroBq4090zSbuCOnD3J81sHnAAcAtwCPAPd383Wc9EwgD79iTkMuAxMzvD3RfnrOpWd68DlpvZMYTB89PJbX8ysx8CPwTOBPYF5gIZYDSwNGdfRURERNZJMQ1W21tXHwwvSP5uSChTwN0fBwYBJOURk5I2C7MD4RRuINQE35L8vTDntuOB/sCsnAF2b+BY4NwmthVgDDAxGRRn9SSUdwBsDfwpZ78WAnrWioiIiHSwLl0m4e6zgJeAHxXQfF1KuW8CdjGzrxFqfO8BMLONgP2AicA2OZeTgePMrLKZ/ucC57j7oOyFUB/806QM427gTHcf7u5fAm5dh20XERERWYsOoCtcV88MQygteNLMriUcdPYO0A/Yn5CZbek0aX2SuuNcy/Mbufv85KC5a4Db3T17OqCjCQfSPZfb3syuIxx4dwih3jffDcBFZvaYu79oZl8EHiBkmf9FKO9YmaxrPHBW8n9FUmohIiIiIh2gS2eGAdz9VWA8sAb4P+ATQg3xEcD5wJdbCP9/Sdvcy3HNtL2eUL97A4SBKfBj4OYmtmkFcBchQ/yp8gZ3v50wUL/FzFYQMs9nuvstySwUpwK3mdlyQpb4BqAe2LKFfREREREpiA6gK1x3yAyTzOJwYnJpypTkkhtzGHBYC6td61FMZqUoy7leRzhwrrltyp3qrakB8bXAtc3EXkzIcue6tIVtFREREZF2UJYppqKPEnHJqEM65EEbXdsY1X5Qpj66jxVl8d/H/l0VHcI+tdXRMYsaK1tvlGd1WfyPLd+4eJPomOdO9qj2B1a/Gt3HS5vFT3CyYkn8gzO5vld0zGb0iY7ZoCE+i/HDV85tvVGeIyecGtV+Q+KfZ30y8fvybln8a2BsJv7xrE+RLPrSmobomLoUxxyXRx5a0r8s/j0tjZk94u/nt3vFfwwMTJHJ653i02ZA/MPJBxXxMbE2TlGE+Llen6qsLCxu1n2dnjZ977Nfa/exwqbTH+70/WwLXb5MQkRERESkvXSLMgkRERERKVwm7sfdkqbMsIiIiIiULGWGRURERIpMY4pjC0qVMsMiIiIiUrKUGRYREREpMpkulhk2sxHAdcAuhHNHXOXu5zTRrpz/nthsIPAWcJq7/z25fWvgZWB1TthL7r5L2m3TYFhERERE2tsdwCzCORw2AR4ws7eTE5Xl+iWwL7ArMAc4HLjfzLZw9znABOB5d9+xrTZMg2ERERGRItOVzhBnZuOAicD67r4GeMPMfk84K3D+YHgAcI67z0yuX2dmFwL/QxgcTwBeaMvt02BYRERERKKZ2SBgUBM3LXP3ZTnXtwQ+dvePcpbNAD6XH+juP8/rYyKhXOLlZNEEYLWZedL3k8DJ7v5h2v3QAXQiIiIiRSaTaf8LcBIws4nLSXmb05+1a3xJrrd4OlEzmwDcDZzt7rOSxQuBx4AdgPFAPfB/Sa1xKsoMi4iIiEgavwemNLF8Wd71VUDvvGV9gE+aW7GZHQpcCZzr7hdll7v73nntTgAWAVsA0wvd8FwaDIuIiIgUmY6oGfZ3fBmfHvg2ZTow1MyGuvviZNl44I38hmZWBvyWcODcge7+QM5tw4GfA+e7+5JkcVXyd026vYCyTJLnlu7jN6MPiX7QKlI8zLEhg1Oc+nFuefyGbVsT39HLlfEVQVXEv5H0S3EfDGiIj4n1Yq/66JiRjfHfldPUXVWneL9O83yuT9GPl8W/t177wkWtN8pxzoQzovsYkIm/p4ekeJ6leX1WpHjdpHnveL88fofWy8T9iprm03Foivt5cYofd9O8BvqnuJ/TzM4V/24T/z7QL8X+L+gRH5TmcwDgtNlTO/3otTc33bvdB3jj3/u/gvfTzP4BvEM4aG408CAh63t9XrtJwNHALu7+dt5tPYF3gYcJpRh9gBuAvu6+R9r9UGZYREREpMh0wTPQfZtQ9jAHqAWudPfrzWwU8CawJ/A88AvC+PQlM8uNP8rdbzWzrwOXAHOBMuB+QhY5tW43GDazTdz9/c7ejljddbtFRESk++lqJ91w9/nAAU0snwP0y1mUX1uc3/4twsC5zazzYNjMMkA10EAYodcSprk4fl2muWimr20I3xoqk+uHAZPcfUwTbd8FJrv7lALWOytZzxQz2wD4K2EakLuAscBOhP0qI/xyNh041d2fLnC7LwBGAIcl1zPAl919WiHxIiIiItI+2mpqtT3dvZ+79wVGEQaMU9to3bkGAb3aYb25dgPGAUPcPZt2Pz9n/wYBfyGcDWVggesc0Q7bKSIiItKkDpparSi0eZmEu68ws2uBe7LLzGx/YDIwEpgH3OjuFya3ZYAjCTUiGwIPAb8CrgC2ItSRfA9oJBRbY2YrgZ0L3SYz6w/8jnD2kw2AJcBl7n5xXrtjk3a9gMVmtk8T+1dvZpcBvwY2A/7d0vrN7Ezg4GT94919+2RVXzOzS4FNgdeAw93dC90nEREREVl3bX7SDTMbQihk/lNyvTdwG3CKuw8EvgucaWtXRR8BfJ4wMPwy8GdCScEIQnnCL5N62z0Bkixt9kwko8xsWf6FUN6Q9RtCxnoCYeLnnwIXmtmmudvu7n8gHME4J+ljWhP71ws4HniPMIhtcf3ufh5wK3BrzkAY4IvAV4DhhHn2Lmn+XhUREREpXGOmrN0vxaKtMsP3m1k9YXDdH1gO7JVzezVwsJnVAM8CA909d5KXi9x9KYCZTQdezGZJzewJ4Est9D2nhZrhrHMIs718Qsg+ryHU/25EGNS25jQzy55NpX8S+xN3r1mH9V/i7guTbf0TcGoB2yEiIiIibaitMsP7uPsgdx9AmPPtXGCamW3n7msIJQ0VhFPqLQWmmNngnPiPc/5vYO0JnBvbYDuHA3cAiwlTcOyfLC90vb9J9i9bs7w3MNnMjl+H9S/N+b+WcP+IiIiIrLNMpqzdL8Wizcsk3H2Nu/8OWAHsYWYDgBHufhAwDNiFUBJxek5Ye5dh3wW8nGzHtsBpaVfk7g3u/iDwBP/NfrfZ+kVERESk47RHzXBPMzucMOvCM4RM8QNm9r2kyRxCtndxM6toSU3SR6GzOGQNBlYDDWY2DLg8WZ4qG2tmOxBqm58qcP01QOw2i4iIiKSi2SQK11aD4QfNbKWZrSDMpHAccJC7P+vuCwhnHfkFoaZ2OvA46Q4Ye41QczzPzHaPiDsMOCjp/0XgA+BVwlzChTg92b/sPt4GXApcUOD67wJ2zqtjFhEREZFOVpYppqF9ifjN6EOiH7Q057GPDRmc4rz3c8vjN2zbmviOXq6M/96X5pz0/VLcBwMa4mNivdirPjpmZGP88bVpvl1Xpyg7S/N8rk/Rj5etiY659oWLotqfM+GM6D4GZOLv6SEpnmdpXp8VKV43ad473i+P36H1MuVR7dN8Og5NcT8vjtssIN1roH+K+zlNWWj8u038+0C/FPu/oEd8UJrPAYDTZk/t9ILaF0Z+s90HeBM+/Eun72db6HanYxaoTPH03qIm/u1pSM+a1hvlWFhfFd3HQcfFn0PlB1cvbb1Rnhv3jd//zJq66JhFz8cPUp5eOiw65s2KuE/cEwZ+3HqjPJV94++zyiHxn7Y9B8W/DV335AbRMSeeOzI6ZvLZc6JjYge3Z78wObqPx7c8vfVGeSZsMz865oVX4u/nXU5u8UyqTZp17cLomEP2ix9BZurjnp8NH62K7uOtpwe33ijP4H7xX7oure4fHbN1Y/z77coUQ500X25WR751VqX40lHVI35nTji+vc/zJV2BBsMiIiIiRaaYZntob21+AJ2IiIiISHehzLCIiIhIkSmmM8S1N2WGRURERKRkKTMsIiIiUmQ0V1jhlBkWERERkZKlzLCIiIhIkVHNcOGUGRYRERGRkqXMsIiIiEiR0TzDhdNgWERERKTIpDgRYMlSmYSIiIiIlCxlhkVERESKTAaVSRRKg+FuKE06v39ZfXTMdPpGtV/ZK7oLNr91QXSMlQ2JjvngweXRMctWD4iOqegR/8PU0vLoEPpn4p4FtywbHt1HffxdxqJ5ddExvz19o+iY6qcWRsfUPPKv6Jg+mQ2iYyoiP4Ae3/L06D52f+P86JgZE06Mjnmyd/y7zf9n777jpKrOP45/lmXZBamKKEq1PSpRsceOLdbYYmJDY4kFNWqM8Wc0IjY0lhhjSezGaKxRYyyxt9i7CeqjIlVABAGlbZ3fH+cOjuOWOZfdBWa+b17zYufOee45d+bOzDPPnLl3w8fGRcfMr+4ZHTPmrvixVVbEvQ7OXtg7uo/ZZRXRMeXfxB8RtrIifvu/SfHm0Tf+rSPVa1pF5F0wI0Ufad47p902OUUUrPabVGGyhCgZFhERESkyDTrrRsE0Z7gdmNlKZhZXZhURERGRNrfMV4bNbDwwyt1vzVs+HLjA3Qe1EH94Ej8ouX4KcE5y85nAtcC85HoZ8DVwL3Cau9cUML6VgE+A9YF5ZjYKGObuw1qKFREREUmjQXOGC6bK8PedAFzs7r2ADwHcvWtyWQ7YCtiVkCgXojPQrU1GKiIiIiKLZR6z0ncAACAASURBVJmvDBfCzPYkJK9rAMsBrwBHu/u4vHaTgVWAc81sR+B7v1Jx98/M7AFg05bWD0wExiTNxpjZIcnfXc3sRmBPwgeSq939vFbaXBERESlxOppE4YqlMnytmc3OvQDXAZhZP8K0hgvcvQ8wAOgEnJu/EnfvR0hgj3P3HzXWkZmtDewB3N/S+t29HhiShA5x9weTvzcCngb6AgcBo8xss8W9E0REREQkTrFUho9vas4wMB34gbuPNbMuQD9gRvJ/QZLkGkKS2xl4D3gsWZZm/f919zuTv582s2nAmkD8sZ9ERERE8ugMdIUrlmS4ObXAgWZ2DKESPoYwh7fgA6K6+6KDYJrZisCVwCtmtg6wIMX6Z+VdrwHiD04pIiIiIoulWKZJNOenwMnADu7e3913Bd5OuzJ3/xK4iDAd4getvX4RERGRxZWhrM0vxaIUKsO9gDpgoZmVAbsAhwH/S7MyM+tGOOLEl4SjTWzYwvqrk/97pN0AEREREWkbpZAM30o4HNoYQtL6IfAn4FgzK2hqgpnNTf7MJOt4FdjF3b8xs5bWPw14iDCt4oRW2iYRERGRJmnOcOGW+WS4qZNquPvtwO3J1cMaaXJ28v+tyeV763P356D57wHcvbqF9QPs3cI6BjV3u4iIiIi0jWU+GS5FVSk+7r1QWRUd85MuM6La+6xe0X28N2OF6JiVK+Knuv+V7tExy3WK7+cH1fEngx9XUfBvORdZJRP3e8stq6tbbpRnbHlldMwP6+Lvs4ZxE6NjhlTHj61i9T7RMZ++tDA6Zuu6zlHtNxk6NbqPDzc5OTpmnTevjI7Zb4NfR8d0P3nX6JjJI96Pjnkj/iWN9avj5jhWd4yfE1mbYhplXX2X6Jh16+I7mlEeHcL8FL8s6lkfHzMzMhvpnuJ9cEp5/Ovz5C/TzXBcLVVU61JluHCl8AM6EREREZFGqTIsIiIiUmSK6WgPbU2VYREREREpWaoMi4iIiBSZBhWGC6bKsIiIiIiULFWGRURERIpMg+YMF0zJsIiIiEiRiT+QXOnSNAkRERERKVmqDIuIiIgUGZ10o3CqDIuIiIhIyVJlWERERKTINJTpB3SFUmVYREREREqWKsPLoPkpPsIc0H16dMz9c/pEta+rjO6Cd5gbHbNqWVV0zNTMwuiYqrLy6Bgq48dWleIzaU3k74Q/qIh/cCaUx884q8jEv6Tcd1t8zJxO0SE8fn18zOAUj+fn5XGPzZvv9o3u4/nO8fvMfhv8Ojpm6HuXR8eM3fLE6JjHq7pGx6QxprIiqn19ilmXC1LEVHaMfzwH1bVP1W9Sx/hjEnTNxI9t5bq49nNTvA+umOIsFLdVpTsmw7apolqXjiZRuHavDJtZBzMb2N79ioiIiIjkW+zKsJllgO3d/bmcZb8ELgGOdPc7zWwusJu7vwjcCXwIjGphvcOAZ929TT/+mtmfgF/y/W0YBIwDBrv7+JTrPgw4ClgPqAQmAQ8AF7p7fElUREREpAA6mkThWn2ahJmdR0gud8sml+6e+x3YSoRkeIkzs67AYcANwK+B51px3TcCuwCnAk8DXwMG/B54DNimtfoSERERkXRaLRk2sw7ANcAewDbu/r+c2zLA9sBwQhK4pZkNcfefmtlGwB+AjYE5wJ/d/cKc2N8AxxGS6H8BR7v73KS/k4ERwIrA28BJ7j4mp8+TgROBlYF3gRHZ2xOHAh8TqtTjzMzc3fM27edm9nOgC/AgIWnuAEwF9nL3Z5L+VgEmAusCA4HDgY3d/b2cdY0xs4OAs82su7t/bWbjgSeAvYHP3H2LQu5vERERkaakmCJdslprznAn4C7gYGCL3EQ4l7v/AngRGJ0kwisATwLPAL2BHYBfmtmBOWGrAkOAtQlz0o9Plp8AnALsD/QB7geeNrMeObEHAtsl61hAqMrmOoGQfE8hTF/4VSPD3grYFBiaXP7g7t8A9xKqylnDgVfc/WPggOTv9/JX5u7fuPvp7v51zuKhwJrAbo30LyIiIiJtpLWS4RsIlVsICXGh9iQkqee7e3WSSO4APJ/T5lx3X+juk5PlaybLRxCS6vfdvdbdrwFmEJLjrCvdfWqSvN4HrJO9IZmTvDJhDjPAn4DDzKx33hhPdfeZ7j4NOCdp0wG4CfiJmXVJ2h2WLAPoR5gfvIiZPWlms5PLAjM7NOfmB9z9a3ef3eI9JiIiItKCBsra/FIsWmuaxMvAz4G9gLvM7D13f6KAuL7AJHdfdAQQd/8AwMwsuT4rp30NkD02ziDgcjPLrfZWJMuzvsj5uxbIPVbWiUA3YHzSFUBnQuX5vJx2n+X8PQGoAlZw9/+Y2efAvmbmwABCtRhgWt44cPeds38nUyNyxzINEREREWl3rVUZvs7da9z9PuAqQkK8WgFxk4B+Zrbo44WZ/dTM9m8mJutz4Ch375m9ABsBl7YUaGarEuboDuPb6Q9DCT92O8HMcg/KumrO34OBeYQKNIRK8MGEKRJ3ufu8ZPn9wNaWk2W3QIcDFBERkVaTaYdLsWiLk26cDmwGPGhmW+QkiFnVQHZe76PAFcBvzOwKYHXgShqfu5vvZuAsM3sb+JSQ3N4D7AS80ELsccDb7v5K7sLkCBDnE5Lbp5PFl5jZEUBX4ALCHOPsPvBXYCQhCd8nux53f8jM/gY8aWanJtu5gDD3+TTCNIrcqrWIiIiILAGtftINd68l/IBsZeDWRpr8DTjSzJ5KpkD8iPDDsenA48Cl7n53AV1dSpjv+xjhsGUXAIe5e7OJsJlVAEcDtzUy9m8ICfWpsGgyzOuEI068ATwL/C6n/XTCDwC/cvfX8tZ1BJA9EsYEYC7haBi1wIbu/lgB2ygiIiISraGs7S/FoiyTKaZCd2m4YsDw6Adt7x7tcDrmFE+MYjsd8+BM/NjmlsUfGr1rJu5zbJ8Ur1ppTsc8pCb+83Wa/WZOijNl96+J357/Vbb9q/1mC+ujY1Kdjrl2QXRMe52O+cqa9jkd84rEno45/v0x1emYU9SlBtXFx3yV4nmzoKx4Tsecpvr3Znn8ewfAjePvW+Kp4m2rxucKsQ77/PYlvp2toS2mSUgbq0yxez89Ky6xBTjMJrXcKM9nH64Q1X7Ezt9E93Hp811abpTnJzXLRcf0L4tPHlZc4cvomDSPzbTyuJ3gyw4Z9u80q+WGOaq61Ea1B+i1buQ7GlC544bRMc+eNSU6ZsfnR0THvLvr9dExnSMTgXeqOnLy8XFJ2oaPjYtqD9D95F2jY9Iktqu/fHV0zNl7HRUd8+HY+OfNBkMnR8fULYh7PD/+eMXoPnp1zp9N2LKnOvRouVGeihTvHX1TfFrt3BDf0cyO8f1EvgwyPTYAuPLIypYbLaV0BrrCtfo0CSldsYmwtJ/YRFjaT2wiLO0nNhGW9pMirxVpkirDIiIiIkVGnxcKp2RYREREpMgU0w/c2pqmSYiIiIhIyVJlWERERKTI6Ad0hVNlWERERERKlirDIiIiIkVGleHCqTIsIiIiIiVLlWERERGRIpPiRIAlS5VhERERESlZqgyLiIiIFBnNGS6cKsMiIiIiUrJUGV4GfZ3iI8zCFCdmnD2lc1T73j3nRffRMLc+Oma5TPwd0KOhNjpmWllVdEz3hQujY7btOjM65j9zV4hq/+r85aP72H3VydExED9J7f2R46Nj3qvqEh2zzZ8ujo7ZekGP6JjPOsW9rI6/fnp0H/Ore0bHTB7xfnTM41Vdo2PO3uuo6JgVH7opOuaxoSOjY9acGffY1MyPf4vsXF4XHTNrQfxrzcLK6BC6pDg/71oNC6JjphC/PdWRLx3dU2xLxxSvTw3Tv4rvaCmhynDhVBkWERERkZKlyrCIiIhIkUlRPC9ZS2UybGbjgZWB/O+bHgO6Ai+6++g26neUu9/a2usWERERKVVmthJwI7AtsAD4s7uf20TbI4HfASsBbwPHuvsHyW1dgWuBPZPmfwd+5e7x8yETS2UynDhOSamIiIhIvIal7zjDdwHjCcXO1YBHzexjd78zt5GZDQP+AOwCvAuMBP5hZuu6ewa4GugDDAa6Aw8BpwEXpR3Y0pwMN8rMngOec/dRyd8TgB2AWmBdoD/wR2Bz4GvgZuAid683s1HAUKAG2B34Aji/saTbzPom69mM8Mnkc+Bcd789uX014ErCJ5yFwJ3Aae5eZ2ZrNjOGvsBNwA+B+cCrwAh3/7L17iURERGRpYOZrQEMA1Z29wXAGDP7I3ACIX/K9QvgTnd/LYkdCYwAdjSzl4CDgG3dfQ4wx8zOA65iMZLhYvgB3TBgU2AjoBx4CngfWBXYEdgf+E1O+72Bl4BehAfhOjPboZH13khIVtcFugF/Ttp2NbMK4AlgKrAKIcH+EXCamS3XwhguBmYQEuy1CZ9qTlrM+0BERERkkYZ2uJhZTzMb1Mgl/5A3Q4CZ7v5FzrIPgfUbGfoQYEz2irvXAx8nbdcCOuXenqxnVTOLP2xSYmmuDF+bfGrIqnP33o20+7e7TwMws58BFcCZSSl9nJldAFxBSEIB3nH3K7OxZnY/cCjwTN56jwVmA9WEavM3QBdgeUJpfiBwirvPB+aZ2Y8Jc5z3aGEMC4HtgJ8RkuZd3V1HQBEREZFlzSnAOY0sPxcYlXO9G6HAmGs+Ia/K11zbbjnXyfu7C5DqWHhLczJ8fIFzhqfl/D2IMI9klplll5UBFWaWPfDhx3nxE4ANG1nvYOD3gAFjc+I6AH2BGUkiDIC7jwUwswNaGMPJhEnhZwJ/A94xs1Pc/cUCtlVERESkRe1UZfsjcGsjy2fnXZ8H5J+8oAthKmm+5tpmT2jQOefvbELd2LoKsjQnw4XKPXrI58An7r5OdoGZ9QKWd/eFSXLaLy9+MGFCNzkxFcDDwFnANe6eMbONgUOSJpOA3mbWOZn7gpntRJgQ3tIYNk/W+TszWxk4G7gfWHFx7gQRERGR9uTus/l+4tuY/xHypt7uPiNZti7fne6Q23bt7BUzKydMjxhDKEzWJre/lbOeye5e0slwrkeAy83sVMKvDbsSfr1YTpi7C7CVmQ0nTNjehTCHeNu89VQSPmnMSxLhAcAlyW0VwOvAJ8AlZnY6YerEFcDtwD0tjOFMoM7MjiDMHf4m+V9ERESkVSxNxxl290/M7GXgMjM7gTDV9GTgvEaa3wrcY2Z3AW8SjiYxC3jB3WvN7F5gtJkdRMjVzqbx6nTBiuEHdIskn1B2JiS5UwifIGYAB+Q0exfYF5gJXAYc5O6v561nLnAEMNLMviHMJ34C+BIYkhzLbk/CgzmJ8GA9DFxawBiOI9zv4wgP7maEH9iJiIiItIqGsra/RNqfcNCAicDTwA3ufpOZDTCzuWa2DYC7PwmcCtxCyJ+2BvbMOY7wCMK38B8ScroXCXOUU1sqK8PuPqiZ24Y19nfOsv8SEtGmzHH3n7TUb3IItdvzmvw+5/bPgL2aWE+TY3D3qYRkXERERKQkJPnPfo0sn0j4Fj132S2EZLix9XwNHNmaY1sqk2FpXkWK7z4Gpzgvy+u1jR28o2mTKuL7OGmT8uiYu176JDrm1OfjDz/Y8OYT0TETznsnOubzWd1abpRnTOf8kzM272c1NdF91NfEf+yf9GrXlhvl+aTRHxM3ry7FF4DjH4t/uasl/j74rLw+qv3wveOfA2Puiv9S742qltu0hg/H9omOeWzoyOiYw95t7NvV5tXeeVlcQHX882b+1V+03ChPZUXc8xnggZrp0TGHl/ePjvlnZafomBUy8c+b6tjndIf4PjqleO8sq0rxxraU0GGqCldU0yRERERERGKUVGXY3Uct6TGIiIiItLWl6Qd0SztVhkVERESkZJVUZVhERESkFDSoNlwwVYZFREREpGSpMiwiIiJSZHQ0icKpMiwiIiIiJUuVYREREZEioxnDhVNlWERERERKlirDIiIiIkVGc4YLp8qwiIiIiJQsVYZFREREikxD2ZIewbJDyfAyqFOKWfHeKT7m0J5fRLUfN61XdB9lvfpGx6xVuWJ0TN19N8TH+NTomN6D66JjFn4U/zTsmekW1b6yY310H8tZeXRM13UWRsd882j8zvlWWUV0zKA94u+Dz++Nf7Itn4l7PDN18V9mVlbE72frV8e/M46pjL+fNxg6OTpmzZnxz4HaOy+Ljqk46LTITqqj++Dq06ND6hviv6Qd0ql3dEx5/G7D2rXxrwPzUnznPD8ypmuKOQBTy+Ofz+VDfxDfkSxzlAyLiIiIFBmdga5wmjMsIiIiIiWrXSvDZjYA+C2wK9AHqAZeBS5z92facyyFMrO1gTOBnYBuwDTg78Bod0/xHZqIiIhI21JduHDtVhk2sx8A7wOVwG5Ad2ANQmL5TzPbub3GUigz2wZ4CxgLrO/u3YC9CeN/aEmOTUREREQWX3tWhq8DnnT3I3OWfQXcbmZ1QGcAMzsdOBToD9QTks7j3L3azG4FugLrAb2ADYEBwIXA2smyd4ET3f2tZH27AZcm63sNGA90cvfDzawDcDIwAlgReBs4yd3HJOO7Hviru5+bHbC7f2BmBwKXm9kq7j7FzPYkVI/XAJYDXgGOdvdxZnY4cCIwG9gEOAKYAVwBrAl8CTwInO7uOiygiIiILDYlFIVrl8qwmfUDtgT+0tjt7n6Xuz9kZj8lJKf7untPYCtgL+CQnOY7J8vWAmYC/wLuBvoBvYGJhEQTM1sdeAC4CFgBuIqQjGadAJwC7E+YtnE/8LSZ9TCzNQgJ9p2NjPczd983SYT7AfcCF7h7H0Jy3gk4NydkY+BGYGXgMeB24AZ370GYfnEQsGNz96GIiIhIoRrItPmlWLRXZbhf8v+k7AIz2xH4R3K1HJhCqJxu5u6fm9nyhAR2Rk48wKvu7sk6yoEt3P0TM6skJKIzgU2TtgcBb7r7Hcn1f5nZ/TnrGkGY+/t+cv0aMxtBSI4/SJZNa2HbpgM/cPexZtYlGWv+mBcCd7t7Jhn3QmBvM5sIvAD0V1VYREREpP2115zhbEK5SnaBuz/t7j2TCvAvCXOJOwAXmNmXhKkGJ+csz18X7l4PDDMzJ0x/uAZYLad9P3IS8MS4nL8HEaY7zM5egMHJ8ilJm0YPhGtmKyV/1gIHmtkEwIHfAyvljXl6NhFO7JRsx43ALODBpMIsIiIistgy7XApFu2SDLv7eMJ83KNaaHoRIRFd3d3N3X8GfJPXZtH9b2abERLgg929r7vvADyZ03YiMDAvfkDO358DR2WT8iQx3wi41N0nAP8FfpY/SDMbBHxuZj8CslM7dnD3/u6+a7KtTY25EjDgGHdfFRhKmOt8RRP3iYiIiIi0kfb8Ad2RwPNmdj1wGfAJ4cdw+wLnAZMJSeFCoM7Mqghzen9A00du6EX4kd0CADP7ISExzZ4y53bgbDMbTpj7uwPwE76dB3wzcJaZvQ18SjhSxD2Eyu0LhIr1v81sGnAt4Udw2fm/zxAS72OAOmChmZUBuwCHAf9rYsyZpP/LzOzyZLtrCFMrRERERBab5l4Wrt0Orebu7wHrEhLXR4CvCVMYfgGMBrYHzgK6EObhTgA2B+4AhjSx2icISeoLZjaLUCW+GuhjZr3dfSKhsns2YTrCqcDThOQTwlEm7iT8qO1r4ALgMHd/IRnz88AwYDPgI2BOMp4HgL2TqQ+3Ak8BYwhHhjgL+BOwppl971ym7l5DSLr3IcxvHk+YknFGy/eiiIiIiLSmdj3phrtPIVRuT26iyWfAds3EH553PQP8OrnkugTAzPoDE93dsjeY2X2EpBV3ryNMzbiomT5fIxy9oqnbqwmV4HxnJ//fmlxyY14GtmhqnSIiIiKLo5iO9tDW2jUZXgL6AM+Z2Vbu/r6ZbU04+90yPT+3LEXMzLL66Jguy9e03ChH5RcpvpT5Jn9KeMu6lsXvtg0z5kTH1H1VFx2TYmj0WmF+dEynmd2j2i+ojR9Y+QrLRcekMbfhe1+gtKiqnb7U6lYWvw9kIl9W67+YF93H7IW9o2OqO8a/ctSn+KK1bkF8PzXzUzxxquNenwCojTxpaEVlfB8pVFbE72dV9e0ztjS6p3grmBP5lK5P8UZY3nKT76utTRMly5h2myaxJCQn3vg/4AEzmwvcABzv7i8t2ZGJiIiItB0dTaJwxV4Zxt2vJcwrFhERERH5jqJPhkVERERKjY4mUbiiniYhIiIiItIcVYZFREREikymqGb1ti1VhkVERESkZKkyLCIiIlJkNGe4cKoMi4iIiEjJUmVYREREpMjoDHSFU2VYREREREqWKsMiIiIiRUZ14cKpMiwiIiIiJUuV4WXQnA7xn/dWzcQ/1C981C+q/cpUR/fx2Z+nR8f8oKFndMy4B2uiY2rqekXHzK2tiI7pWlEbHdMv8mfCL1d0ju6j2z/mRMeUlcXvm3M6lEfHdM+URcdMfjw6JJXe9XHtP3oxfj+bXRa/n9XG32UsSPF79I8/XjE6pnN5XXTM/Ku/iI7h6tPjYyKt8+aV0TF3bDAyOqahIv71dnp5/PNzbln8PrB+TfxzujLyOR2/x0CPhvgnwawb3kjRE3Q+IlVYq9Kc4cKpMiwiIiIiJUuVYREREZEio+MMF26xkmEzewCY4+6H5yw7EbgK+D93vyRn+S1Ad3f/yeL0mdf/MOBZdy9LrmeAhUA9UJb8/w5wjrs/1wr9PQc85+6jGrmtA3AacDgwAKgFXgPOdfdXkjaHAzcD8xtZ/Tbu/s7ijlFEREREp2Mu3OJOk3gU2D5v2V7Ay8Deect3BP61mP0VYjd37+ruywGrEMb4eJI4t6UzgCOA/YFuwKrAM8AzZrZGTruJyfjyL0qERURERNrZ4k6TeBS43sxWc/fPzKwHsC2wNfCqmfVx9+lmtjYhOXzEzNYDLgM2A74G7gZGuvtCADP7BfDrpP2nyW0PJ7f1Ba4DhgEzgLuaG5y7zwV+b2ZDgdHAlsl6Nk3GsD4wHfiDu1+X3NYROBs4CugOvAUc7+4f5q47Wce/gd+6+/XJNj/v7h8kTeYDl5jZqsBKybaIiIiItDlNkyjcYlWG3f1z4H2+rQ7vBrzv7m8C7wI/TpbvRJgyUA88B7wB9CUkzjsCl8OiaQSXAscAvYBzgfvMbPNkPXcDNYREeTtg9wKH+k/gh2bWJUlOn07W1Qf4GXCWmR2YtD0bOATYGVgeeBN4IHdlSSL8KHBSkghDSMx/YWb/MLNjzWyomZW7+8nu/lKB4xQRERGRdtQaR5N4hG+T4b2Bh5K/H+LbqRI7EaZI7ANUk1SC3X0CYXrBkcmc2yOB69z9RXevd/d/Av8AjjKzgcA2wBnu/o27TwLOKXCMMwlziHsREt0x7n6tu9e6+3vAn4ATkraHAZe4+4fuXpf08fNkfAAbA08C57n7HdkO3P02QnI/J9mmd4DpZnZhUm3OGmBms/MupxW4HSIiIiItyrTDv2LRGkeTeBS428wqCJXh0cnyh4DTzawLYVrD7wiV4onunlu9HwdUEaq0KwHj89Y/DtiEUA0GmJRz29gCx9iHUJX+ChgEbGxms3Nu75DcBqFiPSF7g7vPJ1S1MTMIif2rwHAzu9bd63PavkyYL52d0rEncEnSd/ZAkhPdfVCB4xYRERGRNtQaleFXgM6Eiuosd/8vgLu/S0gwRyTL/0dIMgfkVFkBVidMffgquX1w3vpXB6YBk5PrubcXelaIPYGX3X0B8DnwtLv3zF6ANQlVXQjJdv9soJktZ2aXm1n2yPhXECreqwC/Tdp0NbN5uT/Sc/ep7n4D4egRGxU4ThEREZHF1tAOl2Kx2MlwUhl9AjiTb6dIZP0LOIlvjyLxSNLneWZWmUx9GA3c5e41hMTxGDPb2szKzWxvYD/gNnefmPRzmZn1TCqv5zY3NjPrYWZnEZLX3yaL7wS2NrMDkz76A4/z7ZSLW4HTzGyNpNo9klDxzlaSa9z9a+BY4Gwz2yD5od4/gb+Y2fbJeqvMbDvCnOR/FHh3ioiIiEg7aq0z0D0CrMb3k+GHCMfcfRjA3ecAPwI2B6YCrwMvEKrHuPtdhPm2NxDm3p4HHOLuzyTrOwiYC0wk/AjviUbG8piZzTWzucBHSV/bZ3/E5u6fAXsAJxKOSPEG8FJyHcK0hruAp4AvgQ2AH7v7dybHuPujhMT6NjPrRDis2u2E+cezknVfRjjaxC0t3YEiIiIiraUhk2nzS7EoyxTRxpSKCwceEv2gVRB/TvbBNXHdrJypju6jV5eF0TGP1/WMjtm5w5zomJq68uiYubUV0TFdK2qjYz5q6BrVflqKXwfsUh5/n5WVxb+efLigR3TMp53i9+d9On3VcqM8X33TJTrmg45VUe3Xa2jsHDzNm9YQ1wfAzI7xtY8xHeuiY/ZZWN9yozydy+P7qayIj2kP67x5ZXTMHRuMbLlRnlcq4l9v+2U6RcfMLYv/Mnz9mvjXzqmRr1FV7ZS67Nf/81Rxq7z8bPyLVCs7dOB+bX4v/W3C/Ut8O1uDTse8DKrKxO97aZ4RyzfEvdlM6VAZ3cegFWZFx8yfHp88za+JT1K7dIpPUufVdo6OmVMXP7YvI9/T1q2OTxw6do9PahYsjN+W1TvOjY75oqFbdEzPlRZEx7w1b/nomBmReUCvrvHjKv8m/hldVx+f2FemSKB7dZ4XHTNrQXxynyYZrm+I2540faRJbA9577zomPc2OTM6pnOK947VauMT2/oU6VFdZEzPFJ+FPuoUn9g3pNmYpYRKnYVrrWkSIiIiIiLLHFWGRURERIpMg2rDBVNlWERERERKlirDIiIiIkWmmM4Q19ZUGRYRERGRkqXKsIiIiEiRKaYzxLU1VYZFREREpGSpMiwiIiJSZHQ0icKpMiwiIiIiJUuVYREREZEio6NJFE7JsIiIiEiR0Q/oCqdpEiIiIiJSssoyGZXRlzVXDBge/aDVlsX3UxnZy4IUfUwsq4mO2bKmU3TMmQvfi47ZrNvg6JiVyzpHKlBPtQAAIABJREFUx5QTf8etWxf3pc7cFB97J3eoi46pSvH5ep3a9vlMPqs8PmZmh/jXx+4NcY/nZx3inwOVKe7n2H0G0lWW5qd4OBemeO14oHZSdMyQTr2j2lcRv9Ok+dFSlxT9XPLm6OiYizc+OzpmTln8XjCkNn575kXuN3NSPDcrM/E72icdqqNjAK4bf2+Kvbp17Tvgx22e4D0w8V9LfDtbgyrDIiIiIlKyWiwVmNl4YGWgsTLRFu7+3zQdm9nhwCh3H5QmPi0zGwUMc/dhZjYMeBaYl9fsdeC37v5aK/c9CBgHDHb38a25bhEREZEsHVqtcIV+b3acu9/algNZkty9a/ZvM+sEXAw8YWaD3H3WkhuZiIiIiLSlxT6ahJllgJOBEwkV5HeBEe4+Jrl9Z+BCYB1gOnCRu9/YyHq2AS4C1gO+BK4HLnf3ejNbF/gLsD4wG3ga+KW7zzezSmAkcDDQDfhPctukZL1bAlcC6yZj+7S57XH3GjO7CfgVsDrwZgtjuxXomtzWC9gQqEz63BZYCNwJnJbTzXAzGw70B14AjnD3ac2NS0RERKRQOppE4VprzvCBwHbAqsAC4PcAZrY28C9CItsLGA5caWZb5AabmQFPArcDvYF9gRHAqUmTPwMvAssDmwCbAgclt40GdgO2JySXHwGPmllHM1sBeAS4B+gJnA7s09yGmFlv4BRgKjCmgLEB7AzsBaxFSPifSOJXAYYCP+K7yfD6wGbJePsSknkRERERaWeFVoavNbM/5i37r7tvk/x9pbtPBTCz+4AzkuUHAG+7+83J9VfMbCtgImA56zoEeNfd/5Jdt5mNBn4DXEqoru4IvEWY4zvU3RvMrAw4FvhJdg6umZ1FSFa3A/oBc4HL3D0DvGRmNxOqt4uY2ezkz7KkrzeB3d19gZm1NDaAV93dk3VtBwwETnH3+cA8M/sxYc519leXF7n710n7RwnJvYiIiEir0Ek3CldoMnx8C3OGv8j5uxYWHSemLzAht6G7vwsQCq6LrASMz1vnOGBA8vcBwHmE5HMQ8B8zO54wZWE54F4zy/1GoAIYDPQBJieJcNZY8pJhd+/ZzLa1NDaA3CkOfYEZSSKcXf9YWPQDOoDcecg1yXhFREREpJ219aHVJhGmAixiZsea2Q557SYQktdcqwPTkurvUOBsd189WT4DuDX5vxrY2d17Zi+ESuvfgcnAQDPL3c5+kdvQ5Nhyrucm25OA3ma26ICzZraTmR0T2a+IiIhIKg1k2vxSLNo6Gb4L2NjMDjaz8uTHbNlpD7nuBNYzs+PMrMLM1iNMtfhrUtW9ErjAzKoISeh8QvW1AfgrMNrMVjGzDknF+G1ChfahZBtHJuvdFDg6chuaHFsT7V8HPgEuMbPOZrYqcAVhzrSIiIiILEUKTYb/YmZzG7kc1VxQMj1gD8IP0r4CbiEcpu3lvHbjgF2BwwjV3keAmwlTIyBMk1iH8KO0L4DufJvU/gp4B3iFcKSJI4A93H2su88GdiH8wG02cANwX4HbXOjY8tvXAnsS5g1PIsw/fphv5xeLiIiItKlMJtPml2Kh0zEvg3Q6Zp2OWadjjqfTMet0zDods07HHGtZPh3zbv13a/ME77FJjy3x7WwNSoaXQaMGHtIuD9oaKTLo2ZGvgWkOdJ3mDTpNulWR4l5O84EgzdhmpXgj6BGZpKXZ/tgPUABTU+wEndppbNUpHs+u7XBwz29S7DRpPhCnkWa/SfML4jT9lLfDK+f0FJ10TpGkLSiL7+eMt86PjrkkRQKdJulMs3suF3kXxH+8h84p95mjJt++xJPEXdohGX68SJLhxT7phkhWbCIs7Sc2ERYRWZrFJsKydDOzlYAbCScrWwD82d3PbaJtOXA+4dwVPQjnlzjD3Z9Nbt+AMH12fk7Y2+6+bVP9KxkWERERKTLL2HGG7yIcxnZlYDXCydM+dvc7G2n7W+DHhPNJTCT8VuxhM1vH3ScSTs72mrtv0Uhso9pnsp6IiIiISB4zWwMYRqjuLnD3McAfgROaCOkOnOvu49y93t1vJBxmd+Pk9k0IBy8omCrDIiIiIkWmPY4DbGY9gcZOXDY7OaJXtl0VoerbmCHATHfPPYHbh8D6jTV299PzxjCMMF3inWTRJsB8M/NkbM8Dp7r75Ka2Q5VhEREREUnjFMJZefMvp+S1+2ET7cYB3fju/F6S611a6tzMNgHuBc5x9/HJ4unAU8DmwLqE304+ksw1bpQqwyIiIiJFpp2OFvZHwhmB883OveLuz9HEQUPMbF8g/7ikXYCvm+vYzA4DrgHOc/dF53Jw9z3y2p0EfEk4X8X/GluXkmERERGRItMe0ySSqRCzW2zYvP8Bvc2st7vPSJatC4xprLGZlQGXE344d4C7P5pzWx/gdGC0u3+VLK5K/l/Q1ACUDIuIiIjIEuHun5jZy8BlZnYC4Qy+J9PEmX6Bc4CDgc3d/eO8274C9ge6mdkphArzNcDTyVmRG6VkWERERKTILGOHVtufkLROBGqAa9z9JgAzGwB8AOwGvAb8HyF/fdvMctdxrLvfYWa7AlcAnxOmZjxMqCI3ScmwiIiIiCwx7j4V2K+J2yYCXXMW5c8vzm//ESFxLpiSYREREZEi09A+P6ArCjq0moiIiIiULFWGl0E9Mo0enaRZC+NDWBD5UakyxYfQNDH18SGMq4jvqGOKsQ2qS3FHp7BiXVz7cZ3i+xhYE38HpPl03bs+/j6rTXE3r1zbEB0zrSJ+i2KfnnNTbEvfyMcfYH6KB2dSiidB3xTPgbUamvyRd5P+WRm/U69d2+RhRlvN3LL4/Wy1FON6p1N8P5dsfHZ0zOlvnR8dc/sGI6NjqiP3z/ithxQvNfRO8bqxtFBduHCqDIuIiIhIyVJlWERERKTItMdxhotFmyXDZtYLuBDYC+hFOJPIE8BZzZ0fur0l57R+FpiXd9PrwG/d/bVW7m8Q4fSDg3NOHSgiIiIiS0BbTpO4G1gR2NjdlwM2BCqBJ81sqatIu3vX7AVYHngXeCJJ6kVERESWGQ1k2vxSLNoyKd0aONLdvwBw92nJ2UAuBnolB0r+A7AHYS78Y8AId59rZhnCwZcPAp5y9wPMbBfgAmAtYAIw0t0fBDCzSmAk4Ywk3YD/AL9090k5ldhjgLOAnsArwFHuPqWxgbt7jZndBPwKWB1408y2AS4C1iOc4/p64HJ3rzezWwnHwFuPUAXPJv5XAtsCC4E7gdNyuhluZsOB/sALwBHuPi36XhYRERGR1NqyMnwncJ2Z/cXMDjKz1dx9mrsf7u5fAvcREtM1kks/4LKc+H7J5VgzGwo8CIwmVG1PAm4xsy2StqMJB1jenpBcfgQ8mleB3h0YCqwJrAKc2dTAzaw3cAowFRhjIXN/Ergd6A3sC4wATs0J25kwJWQtYDphSsjUpK+hwI/4bjK8PrBZMt6+hGReREREZLFlMpk2vxSLtqwMH01IIA8ErgaWN7OxhHNK/4dQMTV3/wogqZLmnmHkbndfACwws2OAB939geS258zsDuB4M3sVOBb4SXYOrpmdRUhWtwOy56K+2N1nJ7c/DPwwd7BmNjv5s4xQyX0T2N3dF5jZIcC77v6XpM1/zWw08Bvg0mTZq+7uybq2I5xb+xR3nw/MM7MfA3XJ+gEucvevk/aPApsWeseKiIiISOtos2TY3RuAu4C7zKwMMOBQ4G/A75JmE3Laf563itwpA4OAHXISVoBy4G3CvOTlgHvNLPeAgBXAYL5Nhr/Iua02ic8db89mNmclYHzesnHAgCbG2xeYkSTC2fWPhUU/oAOYldO+JhmviIiIyGIrpjm9ba1NkuFkfu/dwKruPs/dM4SpC2eZ2a58m/j1Bz5NYjYEdnH3i5Pbch/Fz4Fb3H1ETh/9CUntDKAa2Dn3yA9mNoSQsPZphU2aAOydt2x1vpsA5453EtDbzDon1W3MbCdgNcL0CRERERFZCrTVnOEXgJmEqvA6AGbWw8x+TphTew/wFPD7ZHkvwnzhgU2s7xbgYDPbwczKzGxd4CXg6KQC/VdgtJmtYmYdzOx4QtW4byttz53AemZ2nJlVmNl6wBlJv415HfgEuMTMOpvZqsAVhB/XiYiIiLSpTDv8KxZtkgwn1dCtgSnAY2Y2l1BdPRDYyd0/JBz5YT7gwMeE6QynNrG+l4HDCQnzbOBxQiJ6YdLkV8A7hKNEzAaOAPbITk1ohe0ZB+wKHEaoRD8C3Ayc10T7WmBPQnI/iTD/+GG+nV8sIiIiIkuBsmL6NWCpuGLA8OgHbWGac7LXx8fEqkyx+6UZ1riK+I46phjboLoUd3QKnRviBjeuU/y4BtbE3wFpPl3PLo8fW22Ku3nl2oaWG+WZVhG/RbERc1NsS9+6+Jj5KR6cSSmeBKuleHDWalgQHfPPyk7RMWvXlrfcaDF9VBH/CrV+Tfy43ukU30+vTPxOcPpb50fH3L5B/MGRqiOHFv9sTve6MagmTU+w97S/t8+bQTM26btNmyd4b059cYlvZ2tY6k5+IS3rlSIbnJPiPWBD5ka1/6Rhueg+asvin0dfpdiWXg3t83ydkyLhsJr4zGZCRdxTtzrF11ldG+LfBMpT9FNXFv+AptlvVqQmOmZ+fVV0zOzIzemV4r12VornQM8UrxtdM/H3c+wHNYApxN/PK6QY27zI52f3FI9NmsS2PsXL05AUif3MFPtNmsR2+HuNfmnarJs2jOtnZof4/WxhWXzMKilea2TZo2RYREREpMjoaBKFUzIsIiIiUmQ0DbZwbXkGOhERERGRpZoqwyIiIiJFRtMkCqfKsIiIiIiULFWGRURERIpMMZ0Uo62pMiwiIiIiJUuVYREREZEi06CjSRRMlWERERERKVmqDIuIiIgUGc0ZLpwqwyIiIiJSslQZFhERESkymjNcOCXDy6AZ5e3Tz4sduka175Kijxnl8U/WgbVl0THjKuL7qSS+n/ll8f2MqWz7p2HHFNvy36r4HS3NS2/XhviYmvjN4cvyqnbpJ3ZXm5/i+7kUuzMzU+xmK9el6Sf+TqtOcT9Xp9jbYu/rOSkem8pM/MbUpdj+NM+bFN1QneI+uGnDkdExR71zXlT7KzeK76Nrisfm007RIbIMUjIsIiIiUmQ0Z7hwmjMsIiIiIiWrKCvDZpb9OLSGu4/Nu+1y4FTgCHe/1cweA15099Ep+7oe2MDdN2/ktgOBa4F+7j6/mXWsAXwC9Hf3yWnGISIiIpKlOcOFK+bK8AxgeO4CM+sIHAzMzS5z993SJsKJq4HNzGz9Rm47DripuURYRERERJacoqwMJ+4EDgXOzVm2G/AR0D+7wMyeA55z91Fmtg1wBbAm8CXwIHC6uzeY2YrAH4A9gAbgMWCEu79vZi8AvwBOylnv2sDWwBHJ9XWBS4H1gd7Ax8Cv3f2p1t90ERERKWWaM1y4Yq4MPwz0NLMtc5YdAdzcTMztwA3u3gPYCTgI2DG57T6gJ7BGcukHXJbcdjUw3Mxyf65+HPCwu49Lrt8PvAEMTtbzPHB9uk0TERERkdZQzJXhGuAu4DDgZTPrDWxDmDpxThMxC4G9zWwi8AJhDm+DmQ0EtgXM3b8CMLPhQPbYYw8Qqsb7AX83s85Jvz/NWffuwGTC0W0GALMICbWIiIhIq9Kc4cIVc2UY4K/Az8ysEjgEuL+F+bs7AdOAGwnJ6oNm1g/om9w+IdvQ3T93d0/+rgOuI0yVADgAmOruT+ese0NCZfhzQnV6fYr//hcRERFZqhV1MububxCS2z2BnwO3NNU2SZgNOMbdVwWGAr0Ic4gnJc1y5xpvaGZn5KziemALM1sdOAa4Kqdtf+Ae4Ax37+Pu2xCq1iIiIiKtLtMO/4pFUSfDib8Co4Aqd3+1mXYZwo/ufp0cdWIyYarFDHf/HHgK+L2Z9TCzXoT5wgOzwe4+nTCveCSwDvC3nHV3J9zXcwHMbAjwO6DczNKcFEhEREREWkEpJMO3A+vS/A/ncPcaYG9gH2AmMB6YAmSrvwcD8wEnHAliLOF4xbmuIswVvsXd5+Wse0yynnvMbA5wN2EqRgMwJP2miYiIiHxfJtPQ5pdiUZbRBOtlzmUDhrfLg1Ye2b5LiufFjPL4TRlYG19MH1cR308l8f3UpvjaqEum7b8cWJiiizSjSrNjdk2x39S00/cpafqJ3dUa2qEPSFf56FUfHzM3RUfVKe6DuWXxd0Ls5lRE9wCVKZ7PdSm2P83zJs39vFw7pQhHvXNeVPsrNxoZ3Ufsexqke+0E+O2E25f4t74DV1i/zR+9CTPfX+Lb2RqK+WgSRasqxe49P8UbVOwbbpo+0iS2X6TYa3umyDjSPMMXlsVHpXmDir2rl0+R1KRKBONDSJHTpEq4Vq6Lj5mWYl/rGrk9VSkemxkp3tW7p0ie0tzPKT7f0j3NW3aH+B00NoGsT/EcSLGb0TNF0IQUn4hWSPE6mKb2N7ND/Nhik9uT345LngGO3eT06Jit6qpabiTLPCXDIiIiIkVG3/wXrhTmDIuIiIiINEqVYREREZEi01BEhz5ra6oMi4iIiEjJUmVYREREpMhoznDhVBkWERERkZKlyrCIiIhIkWlQZbhgqgyLiIiISMlSZVhERESkyGR0NImCqTIsIiIiIiVLlWERERGRIqOjSRROlWERERERKVmqDC+DqsviY+pbfxjfU5tiXBMq4j+59qmP72hWeXQIPVLcaQtT3AfLNcTHVES2/6I8/n6uIn5jFkRHQG07zWubnOLVbnCKnfrTyH26qkN8H2mqGFNS7AMrNsSPbXqKfjqm2Nc6pdhtpkaOLcXLBj1S3GcfdYp/EejZEL8X1EVHQIqXWxaWxT84XTNxHR27yenRfVz35iXRMZdsfHZ0zNJCZ6ArnCrDIiIiIlKyVBkWERERKTKaM1y4kkmGzewK4FBgPXefmrO8E/AKMNbdf9ZI3BDgAmA7oBMwFbgHOM/dqwvodxQwzN2HNXH7c8Bz7j4qbotEREREZHGV0jSJ/wMmADfnLb8Q6A78Ij/AzLoDzwGvAf2AbsC+wF7ANW04VhEREZHUGjKZNr8Ui5KpDLt7jZkdCLxtZie4+zVmtiNwArClu39tZhlCknsQ8BRwOdAbuNXd5yer+p+ZnQTsnl23ma0HXAZsBnwN3A2MdPeF+eMws18AZwJ9gH8AXdpmi0VERESkJSWTDAO4+ydmNgK4zsxeIlSJT3H3d3Oa9UsulYQfx38IvGxmdwEvAa+5+7PAswBmtjyhevxnYG9gJeB+YDlCor2Ime0AXEVIpF8EjgYOAx5ti+0VERGR0qQ5w4UrpWkSALj77cB9wMvAi+5+fV6Tu919gbvPTuYEb0aoFm+VxE03sxfNbNOk/T5ANUkl2N0nAGcAR5pZ/v17KPAPd3/W3evc/c/Au4iIiIi0ogYybX4pFiWXDCfOAzoD5zRy27TcK+4+190vd/ftCHOLtwK+BJ4ys16ESvBEd889UOQ4oIowFSLXqsCkvGVjU2+FiIiIiCyWUk2G6/P+z7Xoo46ZXWBmz2Svu3utu78C/JyQGK9O+FHegLwq8OpADfBV3ronA4PzlvVLtQUiIiIiTchkMm1+KRalmgwX6l5gCzMbbWYrAZjZKsD5wKfA+8AjhPvxPDOrNLOBwGjgLnevyVvfTcA+Zra7mXU0s58Dm7fXxoiIiIjIdykZboa7vwdsC6wL/NfM5gFvEarCw9y9xt3nAD8iJLVTgdeBF4ARjazvJUJV+Y/AHGB/4Ml22BQREREpITq0WuFK6mgSWe4+HvjeidDdvbFlbxB+JNfc+t4Hdm7itlF51+8mHHpNRERERJawkkyGl3U130vZWzazrLHp0c07ao0pUe1nT+kc3ceAO46Pjhm5353RMeccFv8JNlNbGx+zIH9mTMtqx30dHXPju/2j2v84Mze6j7VHrh4dk2mIv59n3fJedMxtU1aJjjn1L5tFx3wyIv6Lm8mZHlHtTzqxU3Qf026bHB0z+cu4cQHcVhX/eF55ZGV0TMP0/J9XtKysqiI6pnzoD+ICUrwGzLrhjeiYhvr4F/Xzv1ghOmazuvjHpndtQ8uN8qxSFr89n0Y+Dbaqq4ru45KNz46OOf2t86NjlhaZIjraQ1vTNAkRERERKVmqDIuIiIgUmWKa09vWVBkWERERkZKlyrCIiIhIkSmm4wC3NVWGRURERKRkqTIsIiIiUmR0NInCqTIsIiIiIiVLlWERERGRIqM5w4VTZVhERERESpYqwyIiIiJFRpXhwqkyLCIiIiIlS5VhERERkSKjunDhylRGFxEREZFSpWkSIiIiIlKylAyLiIiISMlSMiwiIiIiJUvJsIiIiIiULCXDIiIiIlKylAyLiIiISMlSMiwiIiIiJUvJsIiIiIiULCXDIiIiIlKylAyLiIiISMlSMiwiUmLMrNOSHoOIyNKiLJPJLOkxyBJmZt2AanevaaHd5sDxQH/gQOBod7+wmfaDgVX59kNXBTDE3f/UKgNPwczucPdDGln+qLvvnrdsy5bW5+4vt+b40jCzHu4+p5Hl/dx9cs71Xu4+K3LdQ9x9TGuMs5k+NnD391LEnejuV7fiOMoJ++f7zbTZBFiTsC8v4u63tdY42oOZfQps5O5fR8S8BOwWE9NezOxVd/9hI8s/dve1mojZ0d2fNrNVgT8AXwK/dfdvmumnxde0pWV/bqGvMuAnNL4vn9ceY2iMma3SUht3n7IY6x9ZwPqb3X4z6wBsBwwG/g70dfdxacckS4eOS3oAks7iPKnNbHXgbHc/3Mz2Be4GvjGzHzeV3JnZ3sDNhCf/xkAn4Bgzq3D3UY20/zVwSc6iMiADvAf8Ka9tQ3Jbc9tSnhfzbAExOyRtBwDDk8X7mdmZeU17AI0lvv9J/s/2UwbMAbon1+cAyzfVv5n1Ak4G+vH9N8+Nmht7IcxsEPAQMMTMPiN8OHkup8kHOWMFmJB73cz2d/f7WujmlbyYkwr5MBP5xv5iXh+nuvsfCogbDSzqw8zud/f9CunQzH4EXE94bMpybqoDKpuIORsYBUwDcj84ZoBGk2EzWxO4gsaTjtUKGWshUiTpnWhiO5uxOlBfwFhqafm52WRl2sx6A79093PMbGvgfkKiur+7f5jTbjBwdnJ1QzO7OW9VPYBeTfRxKeEDfX/g2qTdCsBVwOFNxBT6mtbu+3MK2e18j+/vy029b/QBRtL4frZDUx1Fvg5Opul9J3t/L3oviHkfSGyf/N8F2BR4FxibjG1z4Inm1mVm/YBHgQGE/OlV4C0z293dn20uVpZuSoaXXYvzpL4KmJZUBy4AzgVmEaoj36uuJM4F9nX3F8xsuLtPNrPdgMcICUK+XwI/BRYC+wBnEF7oJzSzLTGeS/4fnKz/Zr7d/qOBe3PaTgY2AlYivAjvlreuasKLdb7sC/6pwAbASe7+VVJJv4KQFDXnJmBdwht5N2AisCvhzfc7zOywFtbVWGJzBfAacAihyvOwme2ZkxCX5bXPv3490FIynB8zirwPM02IeWPP7+N3hH2xJflxwwqIybqEkGTNAoYCdxDe6G9qJuYEYGd3fyain1uAb4DL+G7S0aTYBDpNkg48A7xuZv9O4hYlFM1Uxv4JPG1mDzQSk9vPrsn/OwJ7EF47xhISz5HAv5tYf9afgW7J69MVwD2E+/AqYKecPseZ2XTC87qM7+8PXwIHNNHH3sBWZtYlGe8GwBTgs2bGVehrWrvvzykS1YOBzSO/9bkV6EtIBgvalxMFvw4Sxh/jueT/Qt4HcPftAczsVuAWd/9L9jYz+znQ0oePPwEPEz6EzXD3D5IPSRcT3ndlGaVkeBm1mE/qocBAwpuTAdcQqpwXNxMziFDxgORNMHkh6NFE+xX8/9k772hJqqqL/wYJApJUQOKAhG1WVAQ/EBAUERUEJKkgkpPknJEMSh4ByYKAZEkSJCsgCApIOCgy5BwEJMN8f+xb8+pVV1VX1ZDG6b0Wi+l+dbuqu6vv3fecffaJODulvfZIJHJT4CZg+8J7ubrmvEjqib5GxO7pb9cCS+cj2pLOBo7KHfsW8IP0t+Mj4qd158uNezON2RL4eES8lJ5/QdImeFLfqeYlvg58GpgZ2DEilpP0Y7wQFbEh3tQ8UPFaZcRmYWD2iHgZuF3SA8CZkr4SEf+mN2JSfFxcfKvO23ZM2XGLvQPnGBeN17zAl/Hv4JvpXr0bZ0kOqzpfSyIMJlnTR8QrLca0JdBdSPpIYDTwifRfhsrIILBk+v/6heeH3ZsRcTmApCOBxSPiwfSnWyXdgrMNdZmtBdI1TY83sd8BngGeLh4YEdulc90bEXvWvGYR00fEA5KWAp6IiLuTTKZuTWw6p70X9/MJtCOqLwJ39T1qOBYBZo2I51qOazwPRsS9dS8k6VOF4xuvAwUsD6xZeO5kchv4CiwMrBoRb0rKvq8j8eZ/gPEYAzI8/qPLj3oSnGpaEvhbRDwnaXoc8ajCPcD3cFoeAElfx7vwMjwq6UMR8YikkZJGRMSTKWVWCknz4UhQMZ02A9Up3S/g6Ggef6MQYchp0Xas0qXVaNEmxinUl3LPzUL/lPGb6f2/AHw2PXcaJjlFLA5cDZwQEaP6vG6Gt8gVwUbEcZI+C5wj6av0X4S7LL5Nx4zLwv5uFDI8iT+/0ZgYZ5u7WWvGXCBppYg4vcV57gWmpP63VURbAt2apGeb6ZZj5mw5ZAbgqcJzLwLT9hk3BUPR1zsj4omUjXm9eKCkRdI/r8n9exgi4pqSp/8laR0cIb4k6UC3xNKiKrSe0xLejfu5LVE9BdiMZhHrDA9S8h00QJt5ELCeGxPZ/FrwAfybnaRkSKN1IIcnMbHN3xvfxNmBOryI7+sHc8/NCLTdIAzwPsOADI//6PKjvgw4H/gk8EtJH8eRnQtrxuyMSdY5wAcljcI7+zUqjr8aOEPSqsDNwN6SXgIerjnH4XiSuQP4eLrOTYHJZQgeAAAgAElEQVQda8bclY7JT+o7YC1cHq20aAX8FrhI0v7pdeYEtsUygzqMljRfRPxN0hRJC/kGMHnxwIh4KUX0/yjpmIh4tc9rA1wOHCVp11xEZSvgjzhCVPV+/lcwQtJsDJH+iQqPiYiqSPttwK7AXpjkLA38F3i5eGBOlzgV8FNJ22N5xVgUU9E5YnYRcJakAyksmBUkDdoT6FYkXdJkwEcj4uGkn8/WgUci4piacR+KiBcl/Yihe+uxiKiSZF0LHCdpG/y7nwP4Jf1lEn/B6e6v4EzHjDh7VZZBuqrPa1X9rjfHQYOXgfVw9HIrYJma1+oyp7XBuNzPjYiqpPvwZzIJMIuknei9Lz9eGDN7+ufJwLGS9i4ZU3Vd0GIezOEXeD16FvgcJs87AUdXHN90HciwD3CxpDPxZ5fJLH5Sc00Ap+J1cHv8/cyfXqvNBnmA9yEGZHj8R5cf9TrANphMHQx8BvgrnjxKERGXyO4K6wBX4sl06Yi4vmLI5lh2MTGOuPwOF6nUXdcXsCZwJHB4RBwo6Tqctq6KImyGycCmmKiOxJGEbxWOa6tFy2MrrHvcC6f6HsaTcr/U2OHA1ZI+jSfzq3AKs1QWkiKTK+NFogkZzhb0g0iLeErfLYv1ncVo+hSS8hHEqQqPy/SFU0q6J/d46sJjKqr12yzsU8oFgBmmKTyuKjabEkd2x54z97jfBmdrrJc+HssCfo/vm61Ljr0q9+8LKl6vbgw4cpdHz7W1JdAdSfoMeON8JiYXOwI3pj8vJOmO4m9a0pTpmq7HOtmjgcfTn2dJRKdMe7puOs/9DG1ErwBWKjk2j7Xw3HEN/s19Hs8j6xUPjIiu9qAfAZRtOiU9CcwSEXWEsumc9q7dzx2I6m4l5+2H0enc2W93JYYXFdf9zqDlPJggvBkaCRwbEadLugOT0TIZU9N1AICIOCZ9Jz/GcqmHgG9UFZDnsDvwQVxvMGV6D7+hXvYzwHiAARkez5F+1PcCq+Ef9YP0+VFHxH9xVAwASW8A+2ea2Jpxf8f6xCbX9SKwcXr4FNaM9cNzEfFymqQ+mV7nhhS5rjrPdZLmxhKOmfGkdl70Wo39NyIeq5JI9Hkvr+ONQuVmoWLcCZL+ATyBI8mP4RTxATVjrq36W8mxjwPflDRx4fnnga9L+lphyB6Fx7Va7YR1m15PAW0W9qLMpynapu3HIiLuxptAcORqNmDqiLin5NhMl7hMRJxX/HuK6BfHdCFpVxUe9yPQ+eObkvRdgD9HRKZ1fy1Xf/BL/PsubnB3BJ5n6P55NZNMyDULm1BCVIEZIuL/0u93FuChaGBBFRGPkTJOkiaNiBvxBr8RJM0ELATcWBOxPB74WO6cfXW2Lea0d/N+Hk0LohoRJ2b/lq0yI8nkvg68HBE3vE3XNRZd5kH8+b6B35/S69yRfqdl57hOLjz9LvXrQH7MFXhz1ua9vAZsKWlrvKF6MyKeafMaA7w/MfAZHk+hcbNWmx84ICIWk7Qert5+HVixbLFPY7L0WhGvYanGBcAvsqKzNGYlvHjMgn0ZdwU2rpIASLocODUR/Lux9dGrwDURMX2/91sHSc9HxNQqt3EbgXWXxahLX/IbEX0LJ2QLqI9j8jl5lPiYSjogIsqiknWv23rMuwVJI/sdExFlziLvGtI1roltkrbAmY7fFo6ZAvhoengHrorPa7GnAa6PiA9VnKO1/21b1JH0PPlJz92LN8v3pcfPRsR06d9zAldHxOyFMXcCK0SyNZP0TER8OP37M8DvI2KukvM/CcyZSGSb9zMCR+g3xpHXz2FJ0spF4iEX8B6Ei0/PwlrYG7G12UvAd6KkQFfSZcCvI+KM4t/6XFurOe2dRtffmaS1cFZwoYi4TdK62GFlvYj4XcW5JsJZslMj4kFZcz1NRFRqfwvj+86DuWMvwHKZfXGB4jZYxnRGRLQOaORet60VW3H8J3BU+CcRcZOkX2BnjO812egN8P7FIDI8/qJfAUxdVfgBwLVp0dkOE4InseSilAwDx+D05f7AfTgNtSXWp96FK8ynIrkrpMl1B5zS2hmT5i+nc29ScY6dgPPShPVLPBm+QbkFD+k8X8N6wk9S6KhYILefT/+fl+YFLZkF2+S4qv0fDNn2fAnLTCrJsKRpcVrvW3hhXgCnC5eIXlP+9cil6CX9NSK+3Of6Wo+RNDXwsSwCKmmN9N7OjuEexfkxI4EZI+LGdM/smMacGRGnlI1pS3RT9HDGiLg+Lbq75M5R2dBC0g+BSVP0aQas3fsiTs+vV5X2lv1rL8IL86L4tzJK0rQxvIDxQ8Dt6f/QG+0eg/X3+dfu7H+bxvcl0AWS/lu5yr5I0kcBJw5/FWYsLNpnZf8IW5WVXddsQOQe/zU35h/pcy/DAzh6Wixs6ocdsFXg5njeeQZ/zofgDFgehwJz4/e6Co4oH4PlAJvjtPZiJeeYFjgtRbafYLhNXGkmqs2c9m7dz9nvrANR3Q47kNyWXufXKXp7LJZ/lOGXuB4l20D8Gzgo/WYqXXVazoMZtsH35kk4I3ERvr+3K7x2W4/6q+qObYBROPBze3q8Cy6kHgUsXTVogPc/BmR4PEV0qAbP4ZOYTM+DU0qnhwu4TqsZsyKOnN2dPSHrTc+IiI0lnYfTq9mkuDneLd8uacdwRfgyeGEsJcNp4ZgVeD0ijpb0d2C6qC7QARdM3Igje5V6v4wARMS/al6rOOZr6X0ei10e8r65a2HLpzochBfaGYB/4kr1X6fni9GHovNDT6StBK3GpKjGNXjDs7akzTCZzzSqqxY/a0lfwRrxY/DnvBv2W/0NsL+kN2siSY0WdkkL4nTlUfge+jmwAU5l7ynp9Yg4teT1V8fEZNv01EGY5PwQ33/bU78hXD0izk3R0fskfSedcywZTvftPNjh4B/0psZfTWl9cmNa+992INCtSXrCS5Kmj4gn07WunbuGqXH0rYjXcKT1uTRmydyYySkpOkx4Ars83EOvL/GSFWMAfgosERH3Szo6Iv4jaRXg7pJjl8LNG55K0cQHgN3ChX7743mhDF06vTWa096j+7ktUZ2RIa14hhuwPVsVVgG+EJZnEe7e9+30OnUWk43nQUkfjIhXIuJOklQOy5jmwDKmottHq3UwkuSpcM4ZgGci4o0GL/ElvIl4K73eS3IR4uP1wwZ4v2NAhidMZEU3SwN/ST/okVgXWIU56bVRexBHZUjRiKlyf5sRp5VhiAw8jIsPSqGhYhAkgSeYxyXNHtXaPwELN01TqqY7VlR3xfoBvdrZE3CasQ5LAfOkhXlMRIyRtBvlE2c/T+AytB2zB3bG2Co93hr7fh4k6Xs46lXceOyKPVX3TVHhDYFtkpTlXJzG7CHDLRf2XYBdI+KAFOFaP53jWEnn42xED3nA6eqVI+JiSR/ENoM/iIgLkxzgXKrJwydx0RwM+Wb/WXYuGIaIeCK9p6mzRbDwXj8QOXlQGtPK/7Ytge5C0hNuxrrK40v+tgLlUdzbMWk5u+RvS1Ndsf9XclHkFpiGIYeG7HN4gd7PBGDKiHgKINwI6L+ZLCMiXk33Uw+K8pEMstdwFZrOae/F/dyWqN6Fo+z5z2ElhmcAipgc+9Hn8TTuZliHNvPgw5KOBn6Vn/Mj11Y+j8hJYNJn/RUse3oMa+NL7S8lTYo3EGvi7+81SacCG0a9peELeM3L1xbMTu/nMsB4hgEZnjBxJo5YzAJsmlKs51A+QWf4K7Zh2yoiXkuT9QHALTC2iCg/QdyGnSeOYoikrcjQYlKG0fQWf4DTUFUT7r04ut1Ur/WNwuPpcaSzNN2f8DTwVYbaM4PJwaN9zvUGQ9edLZ5TUB59ezewCF6U3kxR4o8xlCa/HFekF7EAqWEJ9gj9MEMRx+uxhrYMbRb2BRhqEvNZHAHNCsJuYChCVMS8DJH3+fF8dlV6HPj+rsKD+DvNm/R/ERfeVGE2SbvT64M9D7lirDwiYs8U9Z2F3la0hxaObUugW5N0HPU+QdKjEXFx7tivY5K2asmpjsNRxnsi4h+5MfNgQlGqW4+Incueb4C/4AzETgzNARtjIl9E8X0Xs0OlXttp89/qu6T5nPZe3M9tiWomSVsHu33MhqOeddmua/B9sFnaaEwG7EfuN1SBNvPgRlj+tUWK9B8aFfKtPCTNgj/jT+Eo9IzAvyV9M4aavuSxB/79L4vXjrmxc8meDAULynAcdq3YD2chZkvHl20uBxiPMCDDEyY2BVbH1cOnyW4MR1DdeQscGb0AeEHSU1iveDewoqTFsFxhudzxW2PP3NWx1dCF2A+5brItVgpPjyOLl9SMOR1byx1DIdJQps2L8mKaa/CiU9WtaN90jtMZsq9bgf5V4xdgPecmwBi5scnBuIV1ER+Q9c/ZYjFx4XGZL23bMVOEnSbAC/ajWfQlZQfKomiThTvcZWPuz6JP1PuatlnYJ81FYxYARhfOURXxnij3twWB28NOKeBoT9317YsXtSOASeXq8J9RHXkDW4pNhivdZ8QbwdWxlrUUcvfC/XNPZZu8W6loa92GQCc0JukRcYGkQ/B7fwiT/5lxDcDuEfHHkuv5jWz7douk6/FvYGb8ez4pSorQ5NTOdGE3mAsYIkMPR/8OkJvhuWMNbP93ByaU3yw5tp+FX1XjmdbfJc3ntPfifm5FVCPiMklfwNmGmbD38xrhzpVV2BT/pp/PrQH/xJmGOjSeByPiNKzl/gSOqJ8l6RH8Wzk5NxcVcSBusrFQmss+hNezg/FcXcRKwCI5onyvXLR9A/VkOJsfdsSf24M4S7h/1YABxg8MyPAEiBQtOj73+F/AwXLb41KbmIi4V64c/ypepB8Abkgprwdwx6y3csffJOmTwI+Av+N04sZRU3EbEUXz+odT5OJ2POGUIZMvbFh4vqx9cRXewIt71XX9WtJo7Em5MCYQS0V/G7Rt8HVnqcfH8GLys5JjJ6fX6iz/uMzLs+2YJyTNlhaAxfPHSvoS5Y1aHpQ0b7jgbkmsH86wMI4qlaHNwv6AJEVElJxjkZpz3IYJ0qV4I5bfNC2P5QOliIjfSnoeL7j3p9fZJi3GVfgqTonODuwTEZtIuohCe/ECfoajh1lHte2wXrWywLADgW5F7CJiD0m/w4RgFtzc5uyIuL3s+DRm7dyYWdP1HxQRPbpkSZ/HDTe2xeRiUUxKRgAbSlqxjEDnzvWvlK36Dm7U8TBwYZTbZGUWftlnVGbhV4bW32WLOe1dv59pSVQl/Rn4dlQ4DlXgFRzVXghvsh7E9nX9tLZt5kFgrPXhZpK2wxKQdYB9JR0X5Q46iwJzRbIHTZKMTaj+rKehV6bxKH0kH2nt3JWcNekA/xsYkOEJECkdfCDt2h6T/jYaE2GAj0v6dJTbOmWTbZ2XZBN8GE9cpYiWLWLVa5c2MU6V1Va8hwvLxuppJc0h6eCI2Kxm2LxYYvBR0qIeFS2fo4MvbYcxpwO/kfQHTGq+D2NTxodg6UIRv8FdwK5Kxy+axvwfdvmoIo9tFvYTgbMlXY2/i6xwcZF0jjL5BpgwninpQXwvr5LG7YoLp9apGEdKc+5ZRuZq8FJEPCvpFZJGN8lA6jZdH4mIs2V/6z0i4hm5McBNVBOvtgS6C0mfvYkUo4D7IqLyM81hB6yZPSI9fj2TTMi66J8yVOjVA1m3uzF2RjgjbYjXobzxTlcP3NbfZYs57V2/n2lPVOeifzv5Iv4GzFuWXeuDxvNgESnCfkLK3u2CP4cyMjwGr0956cVkVHdxvBFHd/OkdifKpThI+lVEbCjpeKprTrr6Sw/wPsCADE+YOIyWbY/lFqxH0dtC80nK7dhaT7bqraCfGFgC27fVjZsf275lhRMn1kzY3y48fhProfdqeI0L4gl5ebwpqCPDF2Of1Sfx59QKcsHadNHC1L3PmF0xqfoJsFdEZAT1bvwZlJGj/XC0ZCFgnRhq5pK19N6v4lLaLOwH4O96IWDNGDL+vwgT9FLyERHnyW2UvwpckCu4WRzYKurbE69DyyYqwL8kfSvcjXGMXOH+Gt5IVuFRuY3xI5JGShoREU+q3MIsQ1sC3YWkny7pP1gDeXxUFCgVcJfcEfIYbBFWlbJehKHmFDBcqvBbhlwzqvALGjojxJC1WEZU64qA8+jyXTad096L+7ktUf09cLmkc+h1+qi6b57DAZOmn3GGTvOgXOS2PLA2/kzOxFmmMlwInJx+J/fjTdJBlEvSwIT6StkV6AG8dkyEI/llGFHx7wH+RzAgwxMmurQ93gUvYi/g6OBBmPBU6Xm7TLbFSeY1nF6t0vIi22GdiQvBbsYL1sWSfhgR5xSPj2SX1gaJYC6HtWQL4AVtaUwI63A/LqCpalldPM8OOIp2gKzjvhQYmSJM3y9b6FuO2T4i1pU0ZyG1O1/kLPPyiIgqv+qZw5ZXpWnFNgt7Osfekr4UEfnIzIw5aUUpIuJPDC9sJCIWrRuTcCImWL+l9/6sci7ZB0f8PoOlCX/Bco/fVxwPlqKcIWlVfH/uLeklhtwSytCWQHchdh/DUefVgZ1kb+9jgXOjuiXxSCwV2gY4TLZiPDYibiocN1UiPhnGRvIi4mlZz1qHLhZebTffXb7LRnNadj+XjJ8xIv6rQsfIPMbhfm5LVDPSt37h+Tp52e3ATZJuoPf910VF286Dn8EE+Mc40vtrYNXCPVXENtjtJBiSy1xCdXHn7XIB6PextOh+LMUp/fwiYoP0z5vx5vG9KoIe4B3CgAxPmGjd9hhH9w7GRW5rR8QtktbEUduySEfryTb6F9aUYXfsWjA2Oi1pWVyN3kOGJU2TaQ8lLYVtf64uI85yY4O1cfR3UkzK5wU2iFTJ3wdPY3P5e+ldPIr+mltg3XMWaT4YT9DL4Ij9bhQ8UzuM2RJ/Xrdi39jsWkqJcOFcD0SuM1lOv/kobkvag4j4k1ykc3/uubqF/eJE1DNrrEYLjlz49318Lw/TVddoIjdN/9+Ymva1hde6QNK8wOMRsZfsnzsd1Xp2sI3cvniu3QJHO6fF0fkqtCXQrYlduK3s6ThCPAN2kdgPu02UNtFIqe39sb/0lzBZOVfS0xHxudyhzypnhxgRx2R/kKv++2U6ulh4tdp8d/wuW81pktbOv/dEhD+bjp2v6iRp3tkQF0AO29DUkM5WRDVayssSXmS4lKpphLTNPHgDLri9Fn/O50SFPVoeKRO2mFx4OiMu9K11+4mIZ4Hj5S6Gc+GGIP3wc1xsPsD/GAZkeMLE3dlELemFRFhepdemKI/H8cT8IKm5Q0Q8oBJf1vS30slWUqWpu6RvYa3kLOl8Z0XE+XLL6CcjoszndG56mwucjzsX5V8785WdS9a/HoSjyXcBG0jaKL9wJTyI04/bp2t5Q1KxUK8O19HfdijDGrjl7V9kv+ZvYXP3f6To75X0NhBoO+ZhSbcBU8gNU3qQX5zSwnIkXvRmklT0IJ6G/gtIm8WjVQQph1GYmN3K8MK8ui6MVWSgdoGPVOQp28XdB1yUiGXV8S8yJBl4imorujxaEeiOxI70PmbDn92PcAOPk+pHjH3v82KyNhUuksvjKlzYWhbFXRfb+NWhi4VXW6L6sRhesPts9GnN3GFO21fSi2HHnhFYlrMz9TaOYBnKInhTVHlvFdCaqKqdvKxrsALazYO3YjlWZTFnEWkzPF1EPB326x4JrCrpgkidNnPHToqlYs9GxLaSvowzfNMA/5S0WB8SfQmwuaSTYsghZID/AQzI8ISJ1m2PcYryVziido+kDTARerrJCeUK8y2wlU9P4w25MOHHwJ+xW8PsWHN6NpYmVPWLf4SCX2x6XNRAHowX4eVxN6jTgbUi4mRJ38VpzSIZfixdx2fT65f5VVYiyrsdTU1vAw+AkRGRFfEtgFO+16fXuU/SR9+GMcun/3ah14Wi7Prvk5sEzIilMcUiw1epbt+doc3i0TiCVMCy2Cbpb31efyyi0C5a0iT4/tsCf9/5v02Micz8eAN1MSaAs2OHjm9FSVvZtEGZF7gtIl5PG6mlcSaisgirC4FuS9Jl27LVsSPI5TiL8PsaiQSyheLq2KrqYaw3/mlJ+voA4Hq5cc5R4YY8M2PitQVuYVyHxs4IkiaKiLeaRjoTGfo9nrtWSM/NAPxB0h+xtKhpA5/aOQ3XJ1wo6SP43poFWC4iqnSsGb4LfCIaFplBe6KqlvKyNGYEQ3r/jECfgHXtlQ1/2syDEbFe+vsUWLJ3UET8U9K26Zxb5L+flGm4FM9Na8pdL3+D3T52lVs+5xu/7IJ1x5mTxYH4/l8D10zsgbOBVVgIf9/7pfs7f+11DVsGeJ9jQIYnQES3tseb4xTsNLi6/XyczqydhJPWb0tMZv9ESUW0pJ/iSMhnIiJyz8+DSduFETG64hQHAudLOgo7XcyJJ9ntCsd9BbdSfS1NrOsz5IRwIS7sGYaI+LTcjGAjvAH4Q3rPTbrDFd/jSLzIr40j8EVt9luSJg5Xf38VuCWb9FMar6wqutWYiLgL2EvSVGULVBkitaCWdF9EFAscm6DN4tEmgpTHJNi9ojVkO8EN8Xf8IbxJKuKXWE5zDr6XN8Gbtu9i0ro3Ba9ZSQtjf9Wpsab3ILzYXgFsJ2myKHFzaEOgu5L0hF2xveJPorwpQRnOx1HqpSPiz1UHRcRtkpbHGuTtc9/7k8BK+d94xfj7UianiTPCNZJWakEcd8AONWMzPDHUze9crD3do+4Fmsxp6XVvknXzl2G7u09lEqA+eIKWBbcdiGoreVnCVjiQsDdDjSq2xYGUMo102XX2mwczHImlednndUk69uB0DRn2wr/9bL7fHTuq7Cw3gtqd4b/NFfGG5M60SVkI+L8Yat9d1L8XsVr/dznA+IgBGZ6AoFy749xz0Kzt8SsRkUVmHklRx8ko6WWfoi+rYwI9EyaQC0bEjRWvvQ6wfskiORnuVPSZqveUpB5vYFK+PE61bxgRxRbBE2eRsjTxPZ8trmGv5KrXvxJXHc+KCfT/YW3eb3DDgX9WXRuApAXwwvl9HIHZjHI7spuAlSSdgSfsfMp2DVKnv7dhDBGxXYqGzUOvxrbY2CPDbyStjDcbwyzdIqJuIWy8eDQl6CU4BRfK7Nt0QCI/m2PpwQfxd3RMBVn5ATbzHy3pBOzC8s1wMdjWDPna5rE/1vIeiqNQhwHfCRe5LYDttYaR4Q4EujVJz+Hj6b7/mKz/HR0R/bI8M2Wfj6SP1B2f3udIbCs2CyZn19ZFqwuYFHeXzAo9R6rcxvFZ4O+SftxnM59hVWDZKHgDp+92HSwT6SHDbeY0SbsUnroWu+JsK7eDr9Oyg4ngfpJ2i+buGG2JaiN5WQHrAMvEUBfCy+XC6/MrzjEWLebBDEsBc2fvPyL+LmlF7HyTJ8PfxAXAT8iyrrly7+EcLIfLY6aIuDP9ewEcMPhrOscjKWJd9R6mwQXkdzTNHgww/mBAhicsjKa83XH+cVWq536GF129IektTLjGPp8Wgg1xZONQPDHdSzlhyPAJynWEn8M7/1oLrIg4gaSPlCvvyyIhxeeKj/tpRR/CVfe7Y4/ejXGRWunnJSlzn/gcJmsv4kW4qvBudxxBGoVTuL9Kr3McXsDLzPO7jCFJXA6h9/df9/2fjDXJdzJcW15VOQ+Ud/wruZ6+Eeeor1b/IrCQpJ1wVC0/blhRqOz1uhXWmJ6NF9OzgFNqonZTZ5mJiLhb0isZEYyIF1TuDvAZYOGIeEvSwfgzujSN+UvajBTRlkB3IekZPiwp+07BncHOwHrNFyrGvCl37Fsd+KCk/+J7bucKecXOwHHRoJ1uHmph4xgR35O0ES4gPAjYpS5lD3wsqgtG/0r55r7tnPb1kuduxJIUqNCyp/k0c0IA2LRFKr4tUW0qL8tjBlxjkcddWM9eig7zYIYP0Dsnv0lvXcvUuddaAHg6kk44Ip4v+W2+njaVr+Ko8I2RCvTSb7K0BkLSV/Dvdyrs9rJ0RHTKRg3w/sSADE9YaNugYk5MtibC7UeLrTqnpFdHuxteyLaPiOfS6/Q71RgcAR5GRiLilJQ2LiXDklYBlEUU5Racd0jaPiKKRSqTyNX5IyoeN/otpEX/t7i9aGlFuKR/4ojMMcB3wx6wy/R53T/LXbfmB67KRd0mxmm9ns1ClzEJW+DoyokVqecyLI3truratY6FpPvoIyfJEdVx9e08hl69dxWuwlZNc0TEY9D4/syjGBUqu/4RkToyJmnO8wWSVjamLYHuQtIzjErv4xN4o/txHGk+kOrmDgdiW8blcmP2SO9l25LjFwZ2kAtWj8G2bU0iw61sHCNilFz/cDzeFP2cHGkqZDtelPThKPfhnpZyOdJutJjTImIYGc426LJP8nOVA8tJdFO0JapN5WV53I5b0B+de25NvAnrQZd5MIeLcDZqC+wDPBsuoixG/5+T9NGIeArfK2O7gsotnYvZi6uBTSSdiC38Ds/9LcuslGFvLPs5FmcH9gK+1/C9DDAeYECGJyDEkEH9xzIikB5/IyJ6GluEtXub4In2CByJzONVeguxfoD1l4/IPqSH019jeytO5xalDeDoZllx0tJ4Us73kX+TRIxku6f84vk0w1vcPld43JPylfTrPtcN5cVw0+CF4780rwYnEZvRhedWf7vH4IK44/pE0Ip4nELUtQ92a3pgdK9Sz8af2OLww7F04wuSsg56rTXgDdDlNdsS6C4kPcPiWCqRbUDvShHZu6kmw8viDVF2H4Sk23HxUg8ZjohvJHnRavh++FWKRh/XJ6rW1saRsAZ0S0yY804pxWzHH3GUt6zBzAb0OmNAtzktI2NnYynOTTiztBQmhqNL3kO+PfpKWCf+uKQVgImi3u2iFVGN5vKyPHYALpVrPEZjAv1ZLGkoQ6d5MGFznLH5J0PR8j/S6xZyHjBK0lk4G7YugKTJMXm+uHD8TnhDvC/eLByVjr8cF9YtUnE9XwGWShnR7dP7GuB/CAMyPFRRDiwAACAASURBVAFBHSqpI+KidNx9TVLeYfuzs+UCmI2wvdeHgB9KOj6G/GnzGAUcLunJiBi7kElaEi+K65WM2QZYNyJOzZ37ZWAPSY/hCMclub/Nml5zxmhuiZOlaT+C0+oX4fTorNjLt6rQZFZcNLYR1v6diPXPTRbQKfH7LfPMLZUKdBhzDY5CldqrVWBb4DRJoyh4wMZQV7o8zgv7ePaFpBsiYsHc42GbtZpxt0fEZ+ui0EWZRLhV8fY41b81LsqZCreJrSL7H5KU9zodUXhchskK2tHJC4/LPHPfCVJehaewvCmfjZmMetLycsnfX6BmHUnyon2AfWTrxCOxBKSu8r6VjaPsBLInLszaBxeNVdlE7gP8Nb3WaVjLPBOWPq0FLFbyHrrMaeB57QKGiNMueMP+K5xpKYVsi7gx3rA8jongwZJmiohDK4a1JarD5GVNEBHXyjacP8Qb6vNwM4zRFUM6z4NZpFeuc5kJeDDKiyR3xEWvx+P23VkB7CP4Hh8WrEibprlwRuTWXKbiOmDzuk1aDNWYPCW7tgzwP4QBGZ6wMC6V1NfKFeKNGhuEnQs2lrQdLubaADcPOC8iVikce1aaZC+T9CheBGfHE+6eEXEuvfgM5ZX/YG3lPhV/+7skRYPClIhYDUDS74EVI2c5lCLTVd2NXsO6wpNkH8uNcJHW+bI+9vSadOmxOL18FcM9c+vQdsxD2PLpCrzY5q+9Spv7KbyAFxfxKp3xMI25pB9ExJkVr/3pwuM78X3aD9l3vFuDY8ci3MzjCOAI2S5sY+BPkm7G0pEjC0O6pK+vK4y7ofC4zEu5LYFuTdJlzTR4U3y+rLO+Dxe5/ZzhkcVsTFZ4eyLeEG2eG7M/TrlXnW8yhjrdLY5rA4p+2UU0tnFMMqFT8P2yZFQXgAJj5STfxhHBjRiKOt6O2zlXugm0mdMSvoQ13Fm0/6X0effbjK8PLBqpODcizpT0D9xauJQMNyWqkqbHlmrzYcnBOk02rRpqTHFHROza7/h0TeMyDyLbol2e7umDJD2JpSpjNe1pfFkL5ZWBayKiR/aSJERb4ABCVlTdr0V4Ee/mxnWAdwEDMjxhoVMldUKXxgaZZ+rhOPK7BMMrgfPH7SzpdJyy+xie+M+OoYKQIupSwK9RHXl6HvuWNq3SBi/iyxWeu4RqMj4WYY/Ln6YU7jo4Yn0IvcVBGZYAvhwFH9w+aDtmMoYquZvqdTfH0fBLadb2tvi6v8aLcBlaFTPm8AdoLZMYhnBx11WyD+4GOHp3ZOGYvhmREvw7ItaStEg/gpbD9bQj0BvSqxPth6sKjy8sPF6Q3t/zaIYXdt3B8ELc7+OU9DBIOhZnoJ7GnsTrxvBGF1XYDMudmtg43ox/i4tX6IB7EBHXAp9KEcLpgUei2kWnbHxxTqtqxPMCdm3IN36Ynd7uekVMS29x3r/w59GDlkT1EPzdbYc3KPtTLYvJXj8rHpsaS0W+HS2aYkD7eVDSAVjTOxveGE2HM3SH4Y1I2ZipsNwus5abgnINOLhwduAIMcBYDMjwhIXWldQ5tGpsUEx9A6RdfmU3sjTBNp1k78Ak9bKSvy3OkCVTEbdia7Tr6G3sUKb/BUeqv4/1fxl+iBeoSkjaGOsjX0oL9X6yl2Wpy0PCa7jFcRu0GtNRo/s6buRQ16Uwj64Et2xsFdpEn4dB0p7AsdnGMKVgd5bdQorHXtnvmqK3KchKKaKZWaX1RUQs1uS4HPaKiI9IujgiKtPhhXNMVPf3pLUsol/hbdV3OzmwfF761ARJItNj4xjl7bm3rZEO9MMTWCP67US+vhARf6obkAjXD7Cs5gDg1YhYoeLw44ALJO3HUBHYVjilX4ebcZZur9xzm+FGEsXraUtUv4Uty56VO0qWzZ9FFIvH9qZj8ViLeXBZXAw5BZZ6fB5LH0oLeJOE5TJcOHk//n5+IWnxioDKqcCpsgb8cYavA2Wb175ZmBg03RivMSDDExa6VFJn6NvYQHafyNJN86nXMmsaSqqbO5KNI4GjJa0QETfnXuuLOAX6y4qXehVrf6G8a1QZdsTp4T9jYjwnToH2WxB6WhGHC6KK/p55HAEcKHuMPtXw+hqNkVRWWPcKjkLdFPUFdYcCv5S0S1Rbb9XhnUgrtok+F/FlYOv0nR6D222/GuXuGld1uLa78OJd5sICVNq+1WFMimpmGCFbqC0iaTVKSGlE9LQiLkNKn2+Mo+PDXCuqMg6q6dqXxv1Q0pSSfoAlFaOBi6PCo7Xi/sz/vef95IlwCVGtJLdJXnE51pXOgR1iLpf9iksL1TqMySLsO5J0r1iju3/JsXlsifW/66Uxs+JsTpkcoC1RnSSTRUTEvyRV2qLl0Kl4TL1+y2WomgunD+vElwKeSPKWD1DNWX6JNxm7hJ07RuAs54GUf24bpf9/v/B8lexrXJw+BhgPMCDDExa6VFJn6NvYIOw+8QTWrI2gd3F+Eqe+iriq5rxV5zpF0kI4ypu1750JE9VfR8SoinGtOwhFxDmyjdoqeFG/ElgzImojw3TrY78WMBLYQM09RpuOKWtqMTGWpdwpu4pUdb5aDRC2Jcr8ULNzlBWDtUE/rWxVk4LO0eeIWErSTJjMbYdT3qfiSP7NhWO7NANZBstXjqH8cy/DVX3+Xlyof45/z5NSLlUag1vTViIRvC1wpuNxnIauhZp17UPS5xgqYn0IR0ZflDvj3VsypN/nVPl+OhDVQ4CfR8QRkp6NiHvkpjI/Z3jzms5jwv61u6b/2uAfuAvhdxki0RdV6GvH1eWg0SY1uhWP9SOQdRK7fyXp3rLAJZImwpuEOyuOnx8XgI9J1zkmZX+GzbspErxWvwxJEUWpVNoIjsQF1VmQY4DxGAMyPGGhdSV1Do0aG0TEdgCS7o2SdrNl6Eg2iIiNJJ2EdWLT4zTZBRFR2nktXdfEmNTOylAntUmAT0fESjWnuwsXpWR6tLLFvIgufezXaPC6ncZERGm6W/ZnHoU3OmtVDN+45TVNIRfoZZiq8Dgf7e+nla3VpReOa4yIeBRHEA+QnUuOwsVLw76bkgxH2WutWXj8GPainrqpprnDAn0wdhl4sOq7rYKkb2AS/I301KpYo1/5Gapd1z5wNuEIUkvgRGj2xBrQbxUPbvseCmhLbr/IkNNCRqDOlR0PqtB6jGyRthGebxbFxHjjquh4wp3AF5tG9TsS1XFBUwI9LtHULXANy8u40O3rWGJS5VP8Ms5o5JuGzECvPnse4JYkqWptjyYXhB6Edc+v4XviXElLVWVQBhg/MCDDExBiHCqpadfYgIjYU9L8mFxlBPLE4g4bxq0DWUTcQH1Eu4gjcZHe05gEv4RtdopNOvLXNxNO530ujZseV7kvGbaOqkKXKHTrYq0uYwrjX0xRpbpK+mENPCR9E3gqqjXkxULMymvsoJV9W5D0scvjQqJFcBRzk5JDWzcFyaX8/1uV/i+SHZW0Sy8Z01PoFRGztbyuLXCG42hMNG7ErZJLSY66de0D/16+kYvWvSVpNxr4VcsuH6sBM2N5xTHFiH0BbYnqU/h3P9aHV9Lcfa6t1RhJ62IHn8OwfOw1LM85gPL7LMOkWBbRBf2IaptN6tsG2St5HYbWghPqyH6SA82RG/8EMEuUdzoEe9SfI9vS3Y8zhHvSm7VYEEtJrpe0aUQc2/Kt7IuLFb+Kgy/349/PYVQT9QHGAwzI8ASG6FhJnUW3JH2MNKHVjZP0HazfPAsXhMwFXCzph5GzKEvoQja66IzBE9ZCuDJ5o4hYVdI2uLNWFQ7E0ZrFEnGcGkdSDwJWrDl/Y5IqN1iYuihBKLxeMWLZekzNtT6S3lfV9S0JHB4R86YFZ5f0/AYR0VMQFENdAaeLEuumRCKyf3cigYzDwp5I0nK48PA44CdR4W0c3QoOu6T8RzPctSF/bE+7dLXr8pfhBLwZ3iLsy92kA99VtO/aB073fxGThQyfwQSiEpJ+kq7xbFw0Nie2dlwlIs6rGNaW3B6Ji9v2BiaWtCLW9tZt+NuO2Rz4XkTcLmnHsI3lMrhJSR0ZvgK4UdLF9Bb5NsmQ1KHxJjWHcSoek7QG1vQegaP0c+OMxuQRcVTh2O0iYt8qvbGsGy/7DHbG38/5eDPxCrYCLMqtXse1AhcDx6aN3q4M71hYtx6ugKP2T0kaExGvyO3AR9eMGWA8wIAMT7h4HcsiZkmL6ilVZABALrT4DZYkjADGSLoaWKGM7GAysHJ+8ZK0LPaEHUaGO5KNqzqMAReQ3JV0j59Pzx1GvexhMWCeLAoW7nnfdwKUK5z3o9ybuUhSMv/eNqnFLmNKIVfs10X5dsdFeiNw04SVcYHYb6mvjh/m+JDO9QHgltzzoynX/+afK1tsuyzs+df/bjS3PastCCou0B1T/m3H7NbhHFthKci/5Fa8R9E/mtiqa1/aLIEr//+QzvNvHI1eD2+Q67ATtoAc2zRH9vXeH0uVytCWqB6MWwVvhu+tvfCm6Bc119V2zIwMkfNsg/Mw/Qt3R+LfxCfSfxnK5EKtiGpHSdq4zi9b4e9zbDGjpAvxd3NU4dhFcPS16pylkqmwn/AactHhdMDjdZKfsLPRstgP/Mfp6Z4NZwkmxdnE7Hiw1WTTtvYDvE8xIMMTIGRvzAuAv2GyMj+2lVqyRiqxP75fhCfqufDi8AvKdaZz01spfD7WgVVd1yTAjyjX8y6fP7arzhh4SNLIiLhf0kdl6563cCFQFUbQ+1uZmP4+lUdiLdt+9G+G8QK0ljx0GdODpIPbDxdYVmGeiDhS0mexK8gfwi2De+z4ZFeRy/B3WOamMCUuCsqQkcDVgK/hQs17ccHVflTIYLrcA5JmTdKWndLjnqh0TWToa4XHH6W++Ut2zjkxESze08MswdpqDvtpkdOmozjmQLyp+TaWSm2PF/+vSSrVDEf7rn3fzv37Tvy5ZZ/dvQxtQqvwMXrvxYvxxqsKrYhqep+H0aBgcBzG3IalAfkNx4pUtEjOnacN+exEVJN++/s0aKI0rvMLns//XHjuOiyBGYaIWDr9v9H7qpIgpb9lr9kjx5BtD/fHkeqf08w7HRy1P1y2zcy+0z2Aa6uHDDA+YECGJ0zshw3wxxJTuXL3EOD/KsYsDXw+IrIuUJEmorsoJ8OPYF1VvlXvVxle4FDEUVjG8BTegb+IycbJxQPHQWd8CnCNpAVx04ZzcUqtzj/5ItxFaROG9GgH09v3vojPY51bmT9qEdcy3DN3i0Rc3rYxFWn1iXGhyX1YC1qFl5NEZhngT4kIf4aSrmBhV5FN0useQa9k4FVyUdyMBKaozudymYa70z0WlHQUrFsIc69dXAjvxJ/ZaIbLD6BPZCgiej4fuUCq0i9VbjKQt9LKznErFd3E2speJI3En3FxEzkPJpZlr/MHHLX9OHaGOAo4RNLJkYpgC8c37toXEcVNQ/F66yRJ4N/bBjginWEVajZrbYmqpOMp/4xfw643F0XE9eM4Zmvgj+k+nTJFQxfG2bV+19dIYzsORLV1E6X0+9+BcgJdpzP+N37PF+Se+w4l2bgGv+kx+XULy35eYKhtdc/x5ORIcvH4cfh7WD8i6jZYZdgcB3WexRmI5/Fc0vc7HeD9jQEZnjDxcXqjLMdT01YVF3S8XHjuZXJaqwIOxG03j8KTxZy4T3zPQpvD97Ce96PAzyJilUQm5i85trXOGCAi9kmk8Hms2zsAex9vXjNsa0ya72VoMbwCp//q8DiOgjYhw8X3sxP130eXMbuVPPcKjtL+JWwFVYXjsH5zGmBl2c/5D3gD1YOIuAhMwFss2FPR+56moLcNcYYuutys9fO4OBfkcSbW01bhZzga+AqOxG2HSV5dFLhIJqfH9+qpFccfjX+fT+HU/C04ilv63eQREf8GtpJdYn6EiXHdb5QY6to3C5Zc7Eqha18ZktRhSyw76peKPiRpTe/BJH8h3Ep9rCY8T8A6ENXXcEe7s/FGcHasB/0jrifYNOnhf9t1TETcJFu+/RD/dh7GThJVDYGy97IGzTW2XWsnWjVRSjgOR3MvoHmreDC5PlPS2QytBd+n3GbzBPqT2zwZPgg7oTyEvZbPipIWzDn8I13Dl6K/NWYPIuJxSQvgNWkk/k5vjHJ/8gHGIwzI8ISJa3GkN79TXxwvolW4EjhM0sYR8XKSFxwClGouI+IYSW/gxWN5vPhvGBG/qznHxBERcuVwlkodRUk3uY4642zsaSlNODuwXp22LB3/NE4jz4PJxv0R8WDdmITDgbMlHUyvHV3xc+vimdtqTAwVQX4+Im4t/l3S1yPiyoqxu0q6FnfculbSbLgAsV+Tizsk7Z7GL4z1ok8BP4iIYivh3+OK8N3w4jYnTkGWOn100eVm31uZJEG2mNuQ/k0RsuMnwrZ2dW2APxIRZ8vtnveIiGckbYqdO7avuMZiShlJf8K/26NLhnwV38uzA/skWcNFVa+fe80PYGvFLJp8Gc06kmXX+TAVXfty55gME/PN8fd5DkN2blX4O8O7rQX2EK5DW3I7EnfHGzsHSjoB2CwiVkz36lEMDxp0GfM0zmw9E/V2anm00dhelf6fEczj8KZ9VhxZrvJM7ttEqQQLYrlUTzaoDmFXj2/j38oX8Vrw9bATUBGtyG1EbCkXQH8bf/8HJtJ9XIXk7yTctbANmS+TUz2W/gOYWS7sa9zSe4D3HwZkeAJCTlrwAUzSzmWosGU5CoVtBWyFF8r/SHoKR2/voiZFHBEn4J1+dv4RkmaIiKoK7wclzZnS7B+RNCV99LxtdMbp+MlwNHg9rDGcL02e364juCkaMGc6x+w5PVqlJRtDkbmi9KRfkUZ2TFs0HTNMXgEgO0mch6OzpYiIP6ZjJ8ME48IG5zoCuzyMwNKSM3Dk5zB6SdFG2IP2IhzpfAVHdrfsd5Kmutw+mAbLMUrJcIV84U3qswqPSvpQ2K1jpKQREfGkpOlaXBfpvFXt0l8Kt9d9hRT5joiLJVVaV0n6Kd5o5i28amUiqi4IHYNrCPLHTo+/zw1wFmZm4LNNonF5LbikSSPitX5jaE9UF2CoADXD5STyGBF/Shu+PBqPkV0K9sYEcgTwptztcPsKEphHG41t5tpyLbB0RIyVpaV5rUieM/RtolSC/+BNR2tExJWS7qKPE1EHckvKaF2ACyg/iteDI9M8dWxEHJQ7dosu18/wIt9icW+TwrsB3ucYkOEJC1nk8EmGFoUZMSmsiiBkeB0vtItgLej9OD3UtPAAPJk/QPWkcTLW834FE63zMCGq8xdtrDNO2Av4FDbAvwhLBP6OyVmxNScAkg7Di/rjDJeFjKHGnzhaNlF4J5HI4l2YJPZUnCdcX3wiRQ+3xWnBs4BLcUHbHMBjctHlP2pOvQCuiJ8emA+TiWco1xq/CKwuaW1Mtp9qEsHposvtiGJRz5vAv6LGhQVro8+QtCq+j/eW9BJOr5ZCva4VE+N7vIpE/Uvu6naJpDGS5sCkZZKa69oTf68XUC11KqJRQaikX2NpwJ+ANbGc5mFMivsibZy2xrrk6eROdr/G7jRVUfi25PYh3GzotNxzq5CifXKhaHHT3miMpEWxZ/XZeF55Gs+Z38Ma4sUi4q81H0FjjW0OX8CWbXn8DevGy9CoiVIBewEnSNqnZEydzea0OCK7dO65SieiNuS2ZOxTsuPJg1gWtj+ONo8r3i5Z1QDvUwzI8ASEcZEW4Il13oi4ou+R9ahM5UfE/rLzwPPApjhqMS313c/a6IzBi9mXUnSOJPlYn3qbtB8BX62KTBQh6Q68CJ4Yycu1AYquC9MUHpctUo3HpGj7Ath26CKGV/yDi9rK0qa/wJ/xubh4ZlO86C6PI3/7UpMdwJrfTC97Z9hrdSoqyJSsRR4beVRNRXgOXXS5jZHJSjoWK22OP6OJcbOL0/F38JOaMWWk+8+UFBEm7IPlJZ/GMoq/4M+3yoYMYHJgVEQ0JcLQvCB0bUxefxkR/4TGvsQZdsASh82xNOAZvLk5hOpGNm3J7TY4O7YhJk4j8WZtpUS+/5SOocOY3YBdIqKYYThF0o5Y21+68U5oo7HNcBf+beZrBnbAG8IytGqilJBp45dL/y/1vy7B/unvTZ2IxqINuZWLon+C54LHcFapKijSCmWyqtx5P8BQLcIA4ykGZHgCREnkaSyi2tT9ORzdaBTdqUGdP+mpWMObLbYbNni9xjrjhCx6DM19Il9kuIaxH07CspJ95MKeURHRr31zaYe9t3NMphOW9Ol+RTw5rIgLbf6dZDZZt8Kn0qaj3+v8BesYv4IX+Bnx91PWifDn2Bv2UXor3OvIcGtdbkt0cfoAxka7s83cU9QsmpJ+FxErR8s2thFxgaxnfzwi9pJ0D95EnlAz7BSGbL+aomlB6AL4Pd+apAGN7csSfgosEbY/PDoi/iNpFeDumjGtyG1E/EF2Q8las18IrBoRD0qaFTfYGVZD0XSMpH2pdhc4DBPXSrTU2GbYDEdSN8Ubg5FYMtTT9jqdY5gtX5LA/CciHqk5R9foaFsnouya+pLblPH6Md4kTYs3Q0v1ibx3htx86Nf4+88Hdt6ge9fAAd4HGJDhCRNd/FJvB26SdAO9XZG6ELkyfBNH99qgrc74SuBQST9j6D3sRq9GL499gaMkHUCh133Z4hER+wL7SloKa5PvlHQZcEhElBYoRYPitrdjTMIISUczpIHOv2ax8nyasOMAEXGnpFci4qn0+HlJ/eaQtfDndw1OzX8BzzvrlRy7Oibal/Z5zSIa63JVb8k3RcXzrZ0+1M32bVi0XtITETFDzTl6rPJyEdgReCNQlfL+HXBFSnk/V7iuqjGNCkJTBuUnabO0DpaqzAhsmchtP93wNAzJSLLP/gXqs0pdyO29OPU/FpI+HPahLrWAbDjmAxHxUs9gxv5mKnX5SSIyXbiQtbSYteJ1r5M77n0Xa+cfAs6LiP+UHS9pfuCAiFhMtjQ8Anhd0opR0eUvbU4mwhKzOfGGaqYGG+vGTkQdyO2/8CbzVCyteA13plwkd92NG+s0wP5Y/vIsnst+i7vctW3rPMD7DAMyPAEiOvil4ujoubnHpQtTfhIqwfR9Lu1U4DRJp+EoVJ5wV01obXXGWzDkEzmppGexJ3JRb5jHq3hyzqe2+6YHI+Ji3IJ6FkwKjk160cMiYlTFsC7FbW3HnIIjr1fQXy9ajOQXK+L7OVg8hiNcGW6kOkU8LS3cDHJoo8utu96XKY9Ad3H62Dn37znoleH0i3ZDveYXUuOQdD1HUr7BqMKv8eb3cpo3HGhVEJo2TftI2g9rnjfEUcHrI2LhmvP8BW9Qd2Los9+Y+tqBVuQ2yXEOpLfwdgYqInwtxnQpfiWR2ctwge7fcEFgG4eC53BUfGKslZ6JwuY9hwNwi+sRWFa0Jq4l2YcKeU3aVFyEi+Amxhr2myUtHRUuNAltnIjaktsRDFkPlrW4frsL2+YFvowj799MGam78eaybQZkgPcRBmR4gAy1fqkt9MZX9fl73UKxUfp/kSzVNUJopDNOBHutiHg0EecFMEl5GLi+T6HWHli/eCnNiUP+Gh8GdpN0II6SHYqlAtm1tS5u6zImh08DM7TQM7eGSjq7FVGy0F+AC6+6GOHndbln4HtgjZJz/jRd37LAxdHc7iqPvmQnIsYWLkl6Nv/47TpP5DxwJR0a7RoIzBoRn2xzMdGxIDTpks8FzpU0L0O/8ypsDlwm++1OJWvwp6OmKUwHcnsYJo534Oj5ZXj+2LHmupqO+YCkr1G9aaoiZ7/EG4GNsH/z/tTrhMeiQFQ/QH+i+kmsTZ8HFzafHhEvpXmyCofi3+jOuLj1zhT93xfPp1XYClvcNXEiakVuu96T44AncQBhNCbGWcZs1nf5OgZ4mzEgwwPU+qVKuiEiFsw9/ljUVM+Py+TUZWwLnfE8wC2SfhARt2OiWEUWi/hgRBze/7DKa1wQFxWthAsRhy1w0aG4rcuYHG7HqdQmpvMfkpS3U5q48LhqYf8bJqRlqIqqTwb8RtIOODMwFiXyjfzfirrcT1Udm8PxVHRnewfQKVL4DuMaSYu0TSGnFP8PcGTsF8AXIueHW3L8ohFxtaznPgCTiTrCCdbIfgrrbufAG9YLq1L+CW3J7Rewtd9I4PCIOFDSdel1Sls4txgzOSWa+Byq7ofFsOzgJUm30Xx+gvZEdQzOGi2NG+68JHcyrKsJWRhLT96UlL2HI7GFXCUi4gG5+UhfJ6L3gNy2xW24ycxeWJ61NNbQv2OBhQHeHQzI8AQItfNLLRb83Al8+J24Lmi/2NJcZ7wgnrSvl7RpRLTReJ2kFkVT4PQs1sCuhfV1pwILR0QpQY0OxW1dxiRsjC2ezqZXL1osoKxr0VyHBbF8Y3ssx2iCf6T/iqglk+pWEHoz7sLVz1IQujl9dMEkklZjKKI4aeFxP1eNNvgnlvD8EVt/9a0BSITmcrzhmAPLbS6X9OOI6Pkc5UKy1fDGaxQmQjPjFHmdi8CdwBfLXrMGbcntcyll/28cJSUibpDbU1eh0ZhxIHQjMq1xRDwkN4FpirZE9UxMtmfBDUk+hX3mq7ocgqVyM+BNR4YZKcwheUhaHH83V8S4OxG9H7A1/uyOx64fv8eZiK3fy4saYNwxIMMTJhZnOMGo80vtopfshLaLbUIjnXGSQWwt6WKs3V0E6xLfzB1Tpc/7FPAz2RYps3nKxsxb8j5Ow0TrEVyYcmyU+GlWoE1xW9cxO2KN8ZcZLvsYgyf4/Ph+nb9KERH/lP2C94mI4+uOlTQ5jmAtAvwV2Dl/L0q6vXhdBXQpCJ0W3zcn4GKw/HdaJERvV4FoPzzO8Pf5ZOFxE51xU0yDdY4ZmvyuDwF+HhFHJOnHPZJWTtdY9vtcDnvZTo4zF/Ph30S/jMSktK/Mb0tu75a0drhT5guSvoCzKXUa+i5jxgVtMgptieqmeKPySrgj59x4rqrz5T4VW/htD0wkBpwfPQAAIABJREFUF+HtQ8XvLG3kTsCbrX0lrRIRZzd/S+8vpAzqkxHxmfR4DtwS/vcp2zjAeIwBGZ4AERFXZf/WUPVyXUvZPN7JlG/bxRZa6owj4vKkF70OVy1D/2K40xjuX9oP02FJxAXRp9VzCdoUt3Ud8y1groh4vN+BsgtGP+3qkhXPXyDpc/2kNZgIfxVbsC0H3CBp4VT4BI721Z2/S0FoY9lLdHftaIWImKPN8RruWNETRU6vWUqeW9QA5PFFYKn07zHpdc6VdGLF8TNExGhJ38Kp+7sSoehXGHgFcGPauBada6o2RW2J6k7AeZKuZEir+wbugFiFRmMqMm/DEBFvd7eyVkQ1SRROgLFrwDMRcXCfc+wOfBC7KUyJpSC/wW4KZdgKN0o5U3as2DKNHe8gF0Ffir/zNSX9EL/3v+MgyxLxDtm5DfDuYECGJzAkPebrEXFAigZcAswhdwT6fkSMq4/wuKDtYts6JSlpA1yYcgYm2X0L4jJJRVrIZ4+I0X2OH+vtKWmqiHhB0qQ4NfxUn/Rvl+K2tmMepbnGrV/r2FpERK2eMGF5YIGwTd1hKcp9oaQFW34OeVQWhEpaAng6kfW7cSQSrE2t1CbTwrVDw23PemQV8LZIK3bP/bsYRYaaSHIiQFtgl5PZMek8Afs0VxG5p3A3wTtyrzM3vZ3aMtwrt31eDrgknXMz+vjs4s3P6HSuTxTeTxUZbktuR+Niu9cj4mhJf8dBgTpbv6Zjss3RkliTuyvuHjcbzkZdUvH64yLHKRLVa4ATKSGqXdeAcFvsLbFF3vR4Lqsj/R+PiDPTv0+k4PQxnmEvrBfeLj3eHWe9dpb0k/S4ylt6gPEAAzI8AUHSFrjAbLP01MG4PfKyOHW+G14g85isoMmcvKjRrInWtEXbxTY7pq/OWG72cBzW1q0fLSrvE5H9BbauekPSfHjR+XZEPFgzbjWsWZyWocrwMZLmqSGJbYrbuo7ZD5OT/emVfQwrqIqInXnn8SFSp7CE9XEU5gRgZVpKc1RfEPp1rI1cOz01M+5gNwIvaGvgLm7Z8V1dO3Zrc81dEBHj0iJ2K9xifG/cOGVu3J75Dap1pkfixg5740LKFfG8UdXJbEvsDPIynneWwF3Rlqm7sGjZdCRhNO3IbdZR89V0zibdJRuNidSpUNKxwKJhNxmAOyTdion6riVDO8txmhLVjmtAfvwCafxswCqS1omIKpI7NiofEa+k3+X4im8C84U7aM6Ju+idlP52Dm9Py+cB3kMMyPCEhTVwP/i/JAL5LeyV+I8ULbiS3onweoa3h72B3naxbxcZbrvYttEZ/wMvmF+K/qb/ReyNdcOLAn/Aury/Y6Jb11Z1C2DFtAj8BC84D2H7uSrC0aa4reuYLGJ6VuH5SqmIpGkwaSxaV306Ir5ScV1NcSuWuxyWrvlN2TP4r5KqKvvz19amIHRLYIOIyNLHb+RkEG9hQjKWDEdH1453S1oxDlgHWCYisoLFy+WCs/OpvjcPxmR5M3yf7IU3mKXfUSKFYy2n5C6RMyfi1gNJ20XEvsXNdg5jImKPir+1JbddOmq2HTM99jPP4yWs1+5BFLrCtYGkD+ICuuPTeS+Q9CSwbgxvDLQG7deA7BzL4sKx3wJfwhmVdSVNEhG7lQx5x+pL3gNMHRFZUGYBnFm6Bxo3HxrgfY7BFzhhYWRE/CX9ewFMGK6HsYv+R4sDImKxd+/yKhfbA2rGNNUZnwRsG/V+wlVYCZPoJyWNSYU669PbSKGIkRFxWSJTI4A/RcRbkqosx6BFcVvXMW2lJQnH4nbXT+I07MO4ev/IDq9VxNbARZIWi4gV0jU+Iek72CKrqjNchjYFoQsypBWH4Qv22fgeHIbo7toB3ZqovBuYgV65wl1U2+GRIo2H0bC5QCIIK1Ao7JRUJZ/5GtaPV20UxmDP7zK0JapdOmq2HXM1cIKkbfEmeE68cbio7sLkLprr4ULAYZvTmms7HP/+j8fSkAcx8R6FZSoZWq8BOeyOZRTXpGDDQ3Lb6D9Qngkp+i1PXHj8dneHeyfxnKSPhhvJLIp/1wBI+gQuEhxgPMaADE9YeEvSxBHxBi5YuiWLpKTIX6VFmQp+w7nn74kSR4WOmCsiGi+2CY10xhFRmfprgElxtTYMTeRvYuJeh2fSRLkScFUiwl/Hmt0qNC5uG5cxSarxz/S974BJ7sHp3ijDEtihYWZg+4hYXi7gWqnFdZYiIm6SNBeO7Oefv13S54F1+4y/KkXfp8eFQK8DpIX9hRjeWOODDO/KtULudV7sE+Fp5NoxDtKKdxO3U4iCp8d3lB8OcuewDbFn97AiuAqS9lusm72T4YVsYyiPPr+YXqtL1LwtUW3UUXMcx6yLC9juTdczAutzN+gz7lgs57oKF8Y2weLAl9NGe2HstfwEvXNN5zUA/z4zEpjNtXemcWUo81vOP367u8O9kzgPGCXpLGBV0pwkO6XsB1z8Hl7bAG8DBmR4wsJNwEqSzgBWZHjkdA3glvzBaVHPNKPzSTqu8HrT4PTx24W7Uqr2GOCMiGjiH9xJZ9wSVwKHSvoZQ4vsbsCf+4w7AC/SbwKLS1oIt4yuagwC7YrbOo2RtDUuOJoGWynNj8nKLJRLCwDeioiHJT0PfDY9dwrWQo8zUtFOmdzgcaqjgUiaCXceWw4TtNclXYhTvTth0pm/b5/AZC5LcV6Re615GK5dLqKRa0dXacW7jB2AS+UCt9GY4H+WoY1lGY7B9ndX4za5/bAU1ln2FA9WYNjnJOmJiJih4dhWRDU6uGm0HZMyE4vI3RhnAR6qqzHIYQngyxFxf4vTTRsRz0haDrgv3OhiMnrlQ63WgALuAb5Hrl1z2tzfW3ZwxwzU+xU74o3N8cCpOZnVI3gNqt2wD/D+x4AMT1jYHaedR+EU2q8AEsldlYIVVVrUn8B+lSPoXWCexAVObxdmx96X22BXgdOwR2+d/q+1zrgDtsBaymexhdWzeBJcum5QRBwl6VLgzbQ4fRRYKCL+VjOscXHbOIxZA/haKgz8AU5PP4QJWhUZHp3pXyVNKekjODI+ec17eUeRruEmvBivj9/DLLjZyfWYIG1cGHYxlmWsU/KSW+LNShUau3aMo7TiHUdEXCvbj/0Q/77Pw5rT0TXDvgt8oqBBrcMTtNuUFueXfhZsY9GWqEqaBPgR5Rr45d/GMfNjF5nZgccknZgV2NXgNeqzR2W4XdIemEhfmPTAe+HmMnm0WgMK2Bnbt50DfFDSKHz/rNHyWsc7RMRzOMtRxMrANQ0DNwO8jzEgwxMQIuLPqeBsfpy2z3ROEwPLRUmDhYjYDkDSvRGx5zt8fY/iSOP+kr6EtZ3nSno6Ij5XMayLzrj1dUn6CtabjsR62esb6o8fBz6cokMAz0taJiLOqzi+dXFbhzEzR8RtkhYD/hsRt8DYNHgVfgVcLemzOEJyBV60r60Z805jJ+DqiPhR/klJJ+GWr1cWJBJg79XbElk4EhPomTFh+R71rZy7OH10aaLybuGfWO+ZWav1i1o+gTfATbEtbmwyiuHSFCLiupLji1HMxh7dHYjqUdjV4imGZFCfAU6uOU2rMUnzfib+Xd6MHQgulvTDiDin5jxHAAdK2i1pVJtg/TTueexU8UUcxR8mY+qzBny/bA3Ijb1E0v/hjeSV+PNdOiLea8nPe4aot+IbYDzCgAxPYEiRn9GF51YvPXj4MXsWoxxAkyhHa6TK6HlxOnsq6r1uu+iM217P1CmNf136D0mTSjooIqoiqUj6EV5Ai9HTJ8mlGvPoklrsMOZhSUti8vBHANm9oTKdHRHHSroDE6JtsDXXtLjg6b3CMriIr4gVMCnoacYREQ+mIp6jMKHPtJy3AItVFN1l6OL00aWJyjsOuYnABbhI60kcHb5P0jdqUvlHAvslktakUO1TOHtSzKC8E1rRtuT2e8BCuFvhzyJiFUlbYpJYhbZjdsdNJ/KygmWxxKqODK+FN90bSBr2h6ho1hERdwGL5Z66GrdBLsOi+Dt/WtKROLr5LM4MVXkgI+lUYL2I2KjqmAEGGF8xIMMTGCQtjP03z09Vy6NwFOHMmgV9XKIcba5tMWxBtgKOvh4L/DQi6qJRXXTGTa9nPvx+R0q6HvheRDwr6dO449NIqmUFYMP7nYEX8AJ0EI58Vy446bxti9vajtkZ6ytfxnKJxbEWboWSY7PX3ycits89tXd6/gj6FwS9U5i+QoIQOHV7ZdmgsJ3YQokQzgo81lCf2cXpo0sTlXcDB2I7soUi4iVJH8IbyoMp3Acasq7LZAybNiRpm2OCeikNmtsAk2h4F72ernpR0VGP9kR14oiIJAP7fHpuFPZcrkLbMXNjeVUe5zPkT1uFNfr8vQdq2ERF0m5Y3zox/n18Mo2ZHNhJ0usRcUjFab5JfYHdAAOMtxiQ4QkIkpbG9lF74En5ABxN+AWwjmxNVhVh7RrlaIPzcQp+qYo0ahm66Iyb4hDsCrA5lmHsKOki/H5vozrykmFWTC5mA9aOiFskrYmjsaUyji7FbW3HRMQ5kj6c/v2KpAex5dIwN4pUnJZV9m8q6TaG6zqnwVKW94oM/0fSrDHUthmAJAGZjUL0tohwM4SH644poIvTRxdpxbuBRfF7eQnGOmlsguUlRXT1RH4duCgimkbEH2f4pqLYVa+yox7tieqDkuZMdREfSYGBt3ADmCq0HfMIdmzIz2VfxdKcSsRQ0445sSvE1cDkEfFCzbCmTVTWwDUCMwB/wt7M96bz3YzntioyfCqWvZyGv6sm9QwDDDBeYECGJyxsC6wTEScljd1qwFoRcXqKfB5Ptdyga5SjEdLCchR2BVhV0qM4Er1n3SLQUWfcFJ8H5g77C/8NR1JWx1G1n0d9K1LwgjEJ1mLOla73AbkbXhXWoH1xW+sxWQQ9FVF9A2t/iyTvGRxtmhGYjF7niFexBve9wqW46K3sPW5Dnwh8B3Rx+ugirXg3MAZ/p//NPTcZJZG/vBRK0kpYp/24pBWAiaK6vfihwC8l7dKHyGXnmaPF9RfRlqieDFyTagEuxLKlV+gtOBuXMQcC50s6iiHHjnUZaulbCtke7VS8+XoJ+wFfLWmJKGngktC0icqHE/m9V9LruPtchrvxb70KmTyi2GhofLJIG2CAUgzI8ISFz+FJFmA+3MwgKwC4FU/WVegU5WiCVLh1PV6MT8KkY06sZVta0gJZBKvmNdrojJtiokyikUjsbMAmEdG00cSNuPBsU+AeSRvgxa3OoL1LcVujMUkWcDJO85+FNaBXYxnHPpJWjoizs+NT8dmX09jLI2KJhu/73cKewN9TlPskvOmYHfgptuma720+Xxenjy7SincDFwInS9oUR4PnxDKeP1QNkDuUbYw9bR/HWYKDJc0UEYeWDFkNELCJCl0C4//bO/douerqjn8CEgwpDxcE5CEEXekWWEvKojSgLAOkFNAqLTQQQCyPSoAughIKEaMN2BhXXJpUFHkToFjkJSTXGB5qWkRKQVZAGvhWQAMYIhKkFAsJgds/9m8yc888z5m5cx+zP2tlJWdmfmfOnXtyZp+9v3t/pbGd+kESuQJVSQvM7FlcW34uflO3HdXTRwqvkXS1mW3Ez8dj8M/5bEnfa/KzLMS1+TviTY6r8CbZhfhnX4tWTVSeNbMjJS0HxkuqPCfPwysZNSnSzxAEI4UIhnuLzSs0pJMByUfGgHdgNypnFspytMiFuMbtE5Xd/+ajgn6Q3qOmRWtBnXGrZDO/6ylPbmiFz+Ja5m3xn2Eprs1rNAYqd3NbjjWX4o0y09IxLANmS1poPm92Ni6jqULS1JRtOwoPOF8Eflhx/nSdlAWcghtH3ENZ1/oIMEWNx4QVocikjyLSim5wAf67FuXz/G587Fw9zsQ/118CSLrNzJ7AA+hawXDdwLLT5AlUzWwqLju4zcyexG/Cx+DXj5o390XWpONajLvQ7YgbwjQz6gGfzzwpSVf6JfUnrW+jc6hVE5W5eOVse0mbqgJm9p/4NT07E5uK12yFS+oWpv6EC3EJ2CxVT20JghFFBMO9xdNmdkDS036cFDgljiAZEdSijSxHK0wDpmUvqJL+YGafwzvyawbDFNMZF+WtHPrH0tD90tzONeZzhres/BKqQe7mthxrpgC7p8/1YVyTeVl67gY881QT846pe/Gg7zm8eXCRmR0mqa5r2WAjaSVwgPnoup2BFyU912RZ0fcqkhkrIq3oBnviWuCJeGl8dZIcNWI7qi3In8Zv9qpQnTFdqdegY+QJVM1NIr4P/F16aFfgnPT6i3HJ0VXtrknrtsSDx9Nw58MN5hMZzm7S6LsRn4gBZY3+VgyUtGRpyURF7s65T41r0CXAQ02SCJfjfRAlN8678Z9vEUPXNxAEHSGC4d7iUuAuM1uJfxGeB2Buqzsfn9Fbl1KWo7RtZmPMbEdJ7bq97dogoHoMvwBXUVRnnIOxqTRcYsvMNpKqbGXT51kXM6vbFd9qc1vBNWNLX4KS1pnZa6UbEElvm3ek1+PruL3uRSlTtRmuRfwGfiM1ZKTf+514pvORQX6vvJM+ikgrusFyYE/5NI5WTUF+jmeUK68TnwVWVr7IzN6Dnxf74tWHL8mtyMfhGeTT6JDGtECgOgs4S2UHsY2Srk/7eofq7GrRNeAB5kHA0ZSb2ubh8p7zG/xYfcBN5g2N/WY2AQ8460pYlMNEpdQwl3msr8HxlDgS76F4La1ZaW5y9BQRDAcjnAiGewhJ15nZenwE0ZGSVqWnvgwslnRZ/dU12QXPErb7xbahQVC9AzUyIp3QGbfAIwwsGz6a2e5nYHNKicW4Drekq8zSqCu+1ea2Imuyso9slrtRMDwZOKbUNJiCm7k0ti/uFifgo7W+DexgZn14YLy8SQYuF1bMxrqItKIbrMYzh3kME2bh2ccZuD57N/z/X9aZ6wr8s7kTlzC9ZGa34ZnEnemsa2XeQPVAvMm2ROU5fwcedGYpsgbc8OKjKs9tfsbMnsL7GRoFwxfg1xCl7bW4DOicBmuQJNxwY7DYnOprxNsMo/nZQVCUCIZ7DEnfxWUHlY/t0cYuGwVQrXI/rj+u5XB3JrCixuOFdcatIungtM+82e+FeID2Aq5hvr1ZUJa3ua3gms3NDSdKv7N3ZbYbBWdvAhMYOIpsAq7RHFIkrcDPkVnm7lon4J9LP95M2SlOIf/UjuHadLQOn1DwDP7/qDJjXbNJSz4a8I/xG4/34gHxshq68UNxbfEqM7sVzxLPwJtwD1djY5O85A1U381AN7xNUqKk0a31nVhkDfhNU/aG9EXKEoiapKrWsSkjPBH4jepYYJvZr2ji1Cfp/Y2ez8Ey4AYzOw9PgrwPr3yEC1sw4olguIdoVr6HhkPt69GyZWoD5gErzOxNfNrFWlyTeireDHNwjTXt6Izz8piZmVpz3ULSLDO7AM8in4pbq94BXKv684+LNLflXTMOD5Yrqdxu9Lu8BbjdzD5PefrAPFyWMqSY2eZ45noqnhWfjJduO/0lXWTSRyETlS6wyU2xVczse5KOB67PPH6PpMrs8LhS1UnSz8zsT3EN+4w8mvsWyRuovoRPnPnv9Jofl54ws0nUrnQUWQM+TeYLDMzWzqHx+LbSfg/Bp3HsAvzazK6WVGvd3Gb76iCfw2+6f0n5WnEfnrAIghFNBMO9xWLaKN8PFpJ+nqYfXIlnGkqsxQPex2ssK6QzLshruFyj5SyofGRRH9CXGudOAi5PTTXXSMo2qxVpbsu1pkiW0sqmFnPwcvPd+HXjrfQec/LucxD4PT4N5Ra8RD+tAzr2WuSe9FFQWjHoSLq4ldelxsRT0ubRZpa9wdyWape3bMC7HjhvEAJhyB+oLscnZnymxr5m4VWlLEXWkNb8xMxOxzOpu+PnaVZWMgAz+1v8PL4D12PvCdxvZtNVYXoEUJKEpHWbJgQlLfUbkjoxYpLUI9AvaUo6J07CrwO3SGo0KjIIRgQRDPcWRcr3H23w9IROHZikPjObiDec7IKXE3/aIHuWW2fcBo8BD5sPsc+WlM9otljSy2Z2GV5WnoubV2SD2yLNbe00xLXKKmAbuZ3wp8zsM8D2wJpBCm6KcBkeYPwl3nW/lZndV6t5qE2KTPo4hfwmKoOGmV3b7DWSTqvYfB7YG2/KehfVbnTraT5CbX2HGlprkTdQnQ88bmZb47KiF/Drzem4/GPvGvvJtSZJQ5bglZpJuEnFTnhF5QctVJjmAEdL2mQaY+4euiDtt4oUcC/C+0FeTe+7wMxmqM2JP0mOdQ/wEK7BPhjvM1kJnG9uBjKojatBMNhEMNxDFCzfr2iy207IJErHt4HqMn49iuiMi7Ie/2IDL8u2jJkdiDcRTcMD6RtwPWuWIs1t7TTEtcqAfaSguG2jlU4iaTYw23yW618AhwNfMbP/kTSpg++Te9IHBaUVg0jp97kDPh1gKfAMXkn5azJSnNQwOR3AzK6SVCvozLKZmR1U8V6bZ7ZR58Yg5gpUJT2fdPJXAD+mPJv6UeCQWnrmAmtex69L1+IB5FJgSUXDcjPey8Cxl+BB/00N1szG9diPp2O+0nwG9DVAu+Mv5+E3b6WZ8hcD8yV9MWWxL8ZHdQbBiCWC4R4jb/l+GDcAFdEZF0LSyXleb2Z74k09J+OzWW/Gp3c0yp4UaW5rpyGuVTp2szOYpDLuJNyFcG9cH/1Ap9+nwKSPIiYqg4akU9MxLAWOrSy7m9kRuKZ5AGb2EUkPADfWqxRp4Ji4raj+7Cu3OzZJo2Bw+wTwkZTx3A1YK2l1k/dpeU3FZ/xByjr22Wb2Ch4YL1WdGcyJZfiosm9VPDad6gC5kp1wjXIl/4FP72iXw4H9JL2Urm0fwCf4gI+1qzufPAhGChEM9zAtlu+HJQV1xoVITTjT8S/B0s3BFsA+ko6rseRp4GU8SO8DNuCl+02BhKpnzBZpbmunIa5Vxps7e9Wlg93qhUjVjUPxz7kPL+He00wClGP/uSd9VFBEWtENDsHn31ZyH9Uj4MCzkltTv9qSDW63aPPYclEkuE3rfsPA6SitvFfLayQ9hTdyftt8xvJZwEx8RFqjm4GxwDfN7BRcC70bLn9YaWabNNEaOPXjSfzmu7K58TjK49naYZsKOdpkYJ2kkkb7tQbTNIJgxBAncY+So3w/bCmgMy7K5bjr3jr8i/7/gA+SGVFXwRhcTz0z/clSlRkrkoHvUtZ+Ax7QDWeexcd3PZDK+p2mHRvrItKKbrAaD8hvrXjs0/ikgAFI2jr93dL5lqpPmNl8SZ/PPm9m32EQTBqKBLeDSaq8fQK/6TgMN13po47ut4KV6U/pXBbQKJMMrjNekjT9q/GxZ/vTGfnCq2a2g6SX8abd+0tPpOx3NNAFI54IhnuIguX7YU1OnXFRPolnZrYH/l7SCUl7/Sd1jmm4SkuK8JakRlrFIUfS+WZ2APCd1Om+FrheUqfOi8I21un4cpuodIGLgFvM7By8MrQn8CHK9uGbSJnvmrrTlPFcLB+5hpntTLnJ7lwze5yBuvNt8WvQqHUsM7Pz8QD4QDyoXQL8o6THWlg7Hq/4TCPZi+PZ+i83akKUdK+Z7Ydng3fGs/mnSOqEHGcJnt2+HW/APiMd6zi8Kre8A+8RBENKBMO9RZHyfQBbSHoyZfj2TY9dijcejXY60YQ3qJjZx/F5x7fjM1w/ACw3sxMlfb8Db5F7akeb0opBR9ISM9sXd4PbFbf6PUluz5zlOjNbI+n+ygdTVeYuXK9a4hXc5n0n3J1uQWZf6/Gmt9HMAlwjPbnUMNkKVnbVfDdlV82JuETrKGviqplkGZe0cdz1+AI+tvA64F9Vdvtbg3+fNJ2oEwTDnQiGe4vc5fsAgBfMbA9Jq81sh/Sl9Q7wR0N9YF1gJEhnLgaOzzSDHY3r4DsRDBeZ2lFYWtEtJMnMbgTejwfq4+q89ELgTjM7WNKTAGb25/iUgieBj1Xscz1+A4CZ/UjS1EH8EYYrM3F5xE9TZnwJcJfqz0UvUc9V859o4qppZnvhWdq9qJZgtaXplzsM1pqNfDzw753S5gfBUDKmv39ENIsHwZBh7rp2Jl72/CpehnwT2FbSlKE8tgDM7FXgPZV64TRd4lVJ23Rg/3/Ax5CVgt4+XItZ2v6hpPGZNesoSyu2x6UV4yStN3fMWydpu3aPrShmth1eIToC18BPxgPiqbXK+WZ2Ca4pLtkfz8cD/gsaafRT2f8o3HDiRfyzyto3j0rMbBv8RuGT+GfwCuXAeEWN16/Cm3+rguYkgfiupL3qvNe/4U2at+GGOJtQhTFHEAS1icxwEDRB0nwz+xXuQDcT+BquuR4yB7FgAGvwJsrK2bUH0bl5yEWmdnTDEKUdFuLubTviTXOr8MksC/FmrwFI+pKZTcAzwQDTJdWaPLEJMzPgXjxT+Rw++nCRmR3WQpZ0xCM317gZuDlNXPg0rtWeSe0KXDuumvum9Z00GwqCniGC4SBoAUk3p2zj7sCMQZpaEBTjG8BSM7sC+DXeDHYGZZOAtijYENkNQ5R2OBKYJOl1M+uX1G9mc2nc2Hc23kQ6AdcKN+PruFHERWn/mwFfwX9fR7R19COApKk+tOLPOPzmYG6dJe24av4WGN/kNUEQ1CGC4SBoQjIk+RowA9gI7Jdm2x4l6fkhPbgASVeb2UZcm3sMPlrq7HoTELpENwxR2mEjPs8Wyse0FTWCqYzRxlV4BnmxmV1ZerBO4+1k4JjSjaOkd1LAXWWEMZowt7w+FL9x/gWu950OPKjGFubtuGp+C7jDzBbhGf9NRFN0EDQnguEgaM483NVsCt4I9Tw+MulS4K+G8LiChKTFwOLStpmNaZBl6wbdMERphz7gJjObCfQnCcQifKpElhU1HtsDODH9u17j7Zt4Frly9u8EXG40mtkOv2Ysk7Qmx7p2XDX/Of394czj0RQdBC0QwXAQNOc4YH9JvzMDeFl4AAAC1UlEQVQzJL1hZmfiJflgeLILrlMdkkBgBMyavgC/eSg5lK0F7sHd0QbQxs9yC3B7akBdjctX5uFNXqMWSccUXJfbVdPM9pH0X/V+R2Z2WpFjCYJeY7hfsINgODAWeD39u1RSfhsvNQfDl6HW5Q5bJP2vpGPxecCTgfdJOkrSK+3u28xKjV5z8Nnmd6e/l+GygTntvsdoRVIfPlv4MHxqx1TcsfDuOkserNxIUyUqWdTpYwyC0UhkhoOgOT8Bvpncukrl7bn4YP1g+DLUUoRhT6p27AqcaGb3S3qoA7tdBWwj6Q3gU8kieHtgTRPNbEBuV83sDd+HmjwfBEENIhgOguacByzFTRTGmtnv8XFeH2u4KgiGGV1yxhsQgKWguFNj7oKBZG/4mm0HQVCDCIaDoA5mdjNwuqQXzezP8HLyRLwh6EFJbzVaHwwumSkHWSZ07UBGFt1wxosALAiCEUUEw0FQn0nAo2b2N5J+gevzHmyyJugeK5o8H0FZNVMoO+M9jDvjXZaeuwE33WiX8Wb2bKMXtGsRHARB0EkiGA6C+hyImwQ8aGbnSrpmqA8oKDMCJjYMR7rhjLcB+GIH9hM0ZwszO5myNGVsZju+44OgBeI/ShDUIckg/sHMlgPXpLL8XHySROk1zw3R4QVBEbrhjPeWpJs6sJ+gOb8FLqnY/l1mu5GjYBAEiQiGg6AJkn5kZkcDP8PHHYEHDTHQPhhpdMMZLyYYdAlJE4f6GIJgNBDBcBA0wczOAhYAt+JZl7cbrwiCYUs3nPH+pQP7CIIg6Bpj+vujxyQIamFmOwHX4jaoZ0fpNwiCIAhGH5EZDoL6PIFbLu8v6ekhPpYgCIIgCAaB6MYOgvrcCHw4AuEgCIIgGL2ETCIIgiAIgiDoWSIzHARBEARBEPQsEQwHQRAEQRAEPUsEw0EQBEEQBEHPEsFwEARBEARB0LNEMBwEQRAEQRD0LP8PtJQQI/H1Yf4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import  seaborn as sns\n",
    "import  numpy as np\n",
    "# 相关图\n",
    "corrmat = train.corr()\n",
    "plt.subplots(figsize=(12,9))\n",
    "sns.heatmap(corrmat, vmax=0.9, square=True)\n",
    "plt.savefig('train_corr.png')\n",
    "\n",
    "#查看影响最终价格的十个变量\n",
    "k = 10\n",
    "plt.figure(figsize=(12,9))\n",
    "cols = corrmat.nlargest(k, 'SalePrice')['SalePrice'].index\n",
    "print(cols)\n",
    "# cm = np.corrcoef(train[cols].values.T)\n",
    "sns.set(font_scale=1.25)\n",
    "hm = sns.heatmap(train[cols].corr(), cbar=True, annot=True, square=True, fmt='.2f', annot_kws={'size': 10}, yticklabels=cols.values, xticklabels=cols.values)\n",
    "plt.savefig('train_corr_10.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.5 相关矩阵相似度大于0.5的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>...</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OverallQual</th>\n",
       "      <td>-0.028365</td>\n",
       "      <td>0.032628</td>\n",
       "      <td>0.251646</td>\n",
       "      <td>0.105806</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.091932</td>\n",
       "      <td>0.572323</td>\n",
       "      <td>0.550684</td>\n",
       "      <td>0.411876</td>\n",
       "      <td>0.239666</td>\n",
       "      <td>...</td>\n",
       "      <td>0.238923</td>\n",
       "      <td>0.308819</td>\n",
       "      <td>-0.113937</td>\n",
       "      <td>0.030371</td>\n",
       "      <td>0.064886</td>\n",
       "      <td>0.065166</td>\n",
       "      <td>-0.031406</td>\n",
       "      <td>0.070815</td>\n",
       "      <td>-0.027347</td>\n",
       "      <td>0.790982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearBuilt</th>\n",
       "      <td>-0.012713</td>\n",
       "      <td>0.027850</td>\n",
       "      <td>0.123349</td>\n",
       "      <td>0.014228</td>\n",
       "      <td>0.572323</td>\n",
       "      <td>-0.375983</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.592855</td>\n",
       "      <td>0.315707</td>\n",
       "      <td>0.249503</td>\n",
       "      <td>...</td>\n",
       "      <td>0.224880</td>\n",
       "      <td>0.188686</td>\n",
       "      <td>-0.387268</td>\n",
       "      <td>0.031355</td>\n",
       "      <td>-0.050364</td>\n",
       "      <td>0.004950</td>\n",
       "      <td>-0.034383</td>\n",
       "      <td>0.012398</td>\n",
       "      <td>-0.013618</td>\n",
       "      <td>0.522897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <td>-0.021998</td>\n",
       "      <td>0.040581</td>\n",
       "      <td>0.088866</td>\n",
       "      <td>0.013788</td>\n",
       "      <td>0.550684</td>\n",
       "      <td>0.073741</td>\n",
       "      <td>0.592855</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.179618</td>\n",
       "      <td>0.128451</td>\n",
       "      <td>...</td>\n",
       "      <td>0.205726</td>\n",
       "      <td>0.226298</td>\n",
       "      <td>-0.193919</td>\n",
       "      <td>0.045286</td>\n",
       "      <td>-0.038740</td>\n",
       "      <td>0.005829</td>\n",
       "      <td>-0.010286</td>\n",
       "      <td>0.021490</td>\n",
       "      <td>0.035743</td>\n",
       "      <td>0.507101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <td>-0.015415</td>\n",
       "      <td>-0.238518</td>\n",
       "      <td>0.392075</td>\n",
       "      <td>0.260833</td>\n",
       "      <td>0.537808</td>\n",
       "      <td>-0.171098</td>\n",
       "      <td>0.391452</td>\n",
       "      <td>0.291066</td>\n",
       "      <td>0.363936</td>\n",
       "      <td>0.522396</td>\n",
       "      <td>...</td>\n",
       "      <td>0.232019</td>\n",
       "      <td>0.247264</td>\n",
       "      <td>-0.095478</td>\n",
       "      <td>0.037384</td>\n",
       "      <td>0.084489</td>\n",
       "      <td>0.126053</td>\n",
       "      <td>-0.018479</td>\n",
       "      <td>0.013196</td>\n",
       "      <td>-0.014969</td>\n",
       "      <td>0.613581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1stFlrSF</th>\n",
       "      <td>0.010496</td>\n",
       "      <td>-0.251758</td>\n",
       "      <td>0.457181</td>\n",
       "      <td>0.299475</td>\n",
       "      <td>0.476224</td>\n",
       "      <td>-0.144203</td>\n",
       "      <td>0.281986</td>\n",
       "      <td>0.240379</td>\n",
       "      <td>0.344501</td>\n",
       "      <td>0.445863</td>\n",
       "      <td>...</td>\n",
       "      <td>0.235459</td>\n",
       "      <td>0.211671</td>\n",
       "      <td>-0.065292</td>\n",
       "      <td>0.056104</td>\n",
       "      <td>0.088758</td>\n",
       "      <td>0.131525</td>\n",
       "      <td>-0.021096</td>\n",
       "      <td>0.031372</td>\n",
       "      <td>-0.013604</td>\n",
       "      <td>0.605852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GrLivArea</th>\n",
       "      <td>0.008273</td>\n",
       "      <td>0.074853</td>\n",
       "      <td>0.402797</td>\n",
       "      <td>0.263116</td>\n",
       "      <td>0.593007</td>\n",
       "      <td>-0.079686</td>\n",
       "      <td>0.199010</td>\n",
       "      <td>0.287389</td>\n",
       "      <td>0.390857</td>\n",
       "      <td>0.208171</td>\n",
       "      <td>...</td>\n",
       "      <td>0.247433</td>\n",
       "      <td>0.330224</td>\n",
       "      <td>0.009113</td>\n",
       "      <td>0.020643</td>\n",
       "      <td>0.101510</td>\n",
       "      <td>0.170205</td>\n",
       "      <td>-0.002416</td>\n",
       "      <td>0.050240</td>\n",
       "      <td>-0.036526</td>\n",
       "      <td>0.708624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FullBath</th>\n",
       "      <td>0.005587</td>\n",
       "      <td>0.131608</td>\n",
       "      <td>0.198769</td>\n",
       "      <td>0.126031</td>\n",
       "      <td>0.550600</td>\n",
       "      <td>-0.194149</td>\n",
       "      <td>0.468271</td>\n",
       "      <td>0.439046</td>\n",
       "      <td>0.276833</td>\n",
       "      <td>0.058543</td>\n",
       "      <td>...</td>\n",
       "      <td>0.187703</td>\n",
       "      <td>0.259977</td>\n",
       "      <td>-0.115093</td>\n",
       "      <td>0.035353</td>\n",
       "      <td>-0.008106</td>\n",
       "      <td>0.049604</td>\n",
       "      <td>-0.014290</td>\n",
       "      <td>0.055872</td>\n",
       "      <td>-0.019669</td>\n",
       "      <td>0.560664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <td>0.027239</td>\n",
       "      <td>0.040380</td>\n",
       "      <td>0.352096</td>\n",
       "      <td>0.190015</td>\n",
       "      <td>0.427452</td>\n",
       "      <td>-0.057583</td>\n",
       "      <td>0.095589</td>\n",
       "      <td>0.191740</td>\n",
       "      <td>0.280682</td>\n",
       "      <td>0.044316</td>\n",
       "      <td>...</td>\n",
       "      <td>0.165984</td>\n",
       "      <td>0.234192</td>\n",
       "      <td>0.004151</td>\n",
       "      <td>-0.006683</td>\n",
       "      <td>0.059383</td>\n",
       "      <td>0.083757</td>\n",
       "      <td>0.024763</td>\n",
       "      <td>0.036907</td>\n",
       "      <td>-0.034516</td>\n",
       "      <td>0.533723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageCars</th>\n",
       "      <td>0.016570</td>\n",
       "      <td>-0.040110</td>\n",
       "      <td>0.285691</td>\n",
       "      <td>0.154871</td>\n",
       "      <td>0.600671</td>\n",
       "      <td>-0.185758</td>\n",
       "      <td>0.537850</td>\n",
       "      <td>0.420622</td>\n",
       "      <td>0.364204</td>\n",
       "      <td>0.224054</td>\n",
       "      <td>...</td>\n",
       "      <td>0.226342</td>\n",
       "      <td>0.213569</td>\n",
       "      <td>-0.151434</td>\n",
       "      <td>0.035765</td>\n",
       "      <td>0.050494</td>\n",
       "      <td>0.020934</td>\n",
       "      <td>-0.043080</td>\n",
       "      <td>0.040522</td>\n",
       "      <td>-0.039117</td>\n",
       "      <td>0.640409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageArea</th>\n",
       "      <td>0.017634</td>\n",
       "      <td>-0.098672</td>\n",
       "      <td>0.344997</td>\n",
       "      <td>0.180403</td>\n",
       "      <td>0.562022</td>\n",
       "      <td>-0.151521</td>\n",
       "      <td>0.478954</td>\n",
       "      <td>0.371600</td>\n",
       "      <td>0.373066</td>\n",
       "      <td>0.296970</td>\n",
       "      <td>...</td>\n",
       "      <td>0.224666</td>\n",
       "      <td>0.241435</td>\n",
       "      <td>-0.121777</td>\n",
       "      <td>0.035087</td>\n",
       "      <td>0.051412</td>\n",
       "      <td>0.061047</td>\n",
       "      <td>-0.027400</td>\n",
       "      <td>0.027974</td>\n",
       "      <td>-0.027378</td>\n",
       "      <td>0.623431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SalePrice</th>\n",
       "      <td>-0.021917</td>\n",
       "      <td>-0.084284</td>\n",
       "      <td>0.351799</td>\n",
       "      <td>0.263843</td>\n",
       "      <td>0.790982</td>\n",
       "      <td>-0.077856</td>\n",
       "      <td>0.522897</td>\n",
       "      <td>0.507101</td>\n",
       "      <td>0.477493</td>\n",
       "      <td>0.386420</td>\n",
       "      <td>...</td>\n",
       "      <td>0.324413</td>\n",
       "      <td>0.315856</td>\n",
       "      <td>-0.128578</td>\n",
       "      <td>0.044584</td>\n",
       "      <td>0.111447</td>\n",
       "      <td>0.092404</td>\n",
       "      <td>-0.021190</td>\n",
       "      <td>0.046432</td>\n",
       "      <td>-0.028923</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Id  MSSubClass  LotFrontage   LotArea  OverallQual  \\\n",
       "OverallQual  -0.028365    0.032628     0.251646  0.105806     1.000000   \n",
       "YearBuilt    -0.012713    0.027850     0.123349  0.014228     0.572323   \n",
       "YearRemodAdd -0.021998    0.040581     0.088866  0.013788     0.550684   \n",
       "TotalBsmtSF  -0.015415   -0.238518     0.392075  0.260833     0.537808   \n",
       "1stFlrSF      0.010496   -0.251758     0.457181  0.299475     0.476224   \n",
       "GrLivArea     0.008273    0.074853     0.402797  0.263116     0.593007   \n",
       "FullBath      0.005587    0.131608     0.198769  0.126031     0.550600   \n",
       "TotRmsAbvGrd  0.027239    0.040380     0.352096  0.190015     0.427452   \n",
       "GarageCars    0.016570   -0.040110     0.285691  0.154871     0.600671   \n",
       "GarageArea    0.017634   -0.098672     0.344997  0.180403     0.562022   \n",
       "SalePrice    -0.021917   -0.084284     0.351799  0.263843     0.790982   \n",
       "\n",
       "              OverallCond  YearBuilt  YearRemodAdd  MasVnrArea  BsmtFinSF1  \\\n",
       "OverallQual     -0.091932   0.572323      0.550684    0.411876    0.239666   \n",
       "YearBuilt       -0.375983   1.000000      0.592855    0.315707    0.249503   \n",
       "YearRemodAdd     0.073741   0.592855      1.000000    0.179618    0.128451   \n",
       "TotalBsmtSF     -0.171098   0.391452      0.291066    0.363936    0.522396   \n",
       "1stFlrSF        -0.144203   0.281986      0.240379    0.344501    0.445863   \n",
       "GrLivArea       -0.079686   0.199010      0.287389    0.390857    0.208171   \n",
       "FullBath        -0.194149   0.468271      0.439046    0.276833    0.058543   \n",
       "TotRmsAbvGrd    -0.057583   0.095589      0.191740    0.280682    0.044316   \n",
       "GarageCars      -0.185758   0.537850      0.420622    0.364204    0.224054   \n",
       "GarageArea      -0.151521   0.478954      0.371600    0.373066    0.296970   \n",
       "SalePrice       -0.077856   0.522897      0.507101    0.477493    0.386420   \n",
       "\n",
       "              ...  WoodDeckSF  OpenPorchSF  EnclosedPorch  3SsnPorch  \\\n",
       "OverallQual   ...    0.238923     0.308819      -0.113937   0.030371   \n",
       "YearBuilt     ...    0.224880     0.188686      -0.387268   0.031355   \n",
       "YearRemodAdd  ...    0.205726     0.226298      -0.193919   0.045286   \n",
       "TotalBsmtSF   ...    0.232019     0.247264      -0.095478   0.037384   \n",
       "1stFlrSF      ...    0.235459     0.211671      -0.065292   0.056104   \n",
       "GrLivArea     ...    0.247433     0.330224       0.009113   0.020643   \n",
       "FullBath      ...    0.187703     0.259977      -0.115093   0.035353   \n",
       "TotRmsAbvGrd  ...    0.165984     0.234192       0.004151  -0.006683   \n",
       "GarageCars    ...    0.226342     0.213569      -0.151434   0.035765   \n",
       "GarageArea    ...    0.224666     0.241435      -0.121777   0.035087   \n",
       "SalePrice     ...    0.324413     0.315856      -0.128578   0.044584   \n",
       "\n",
       "              ScreenPorch  PoolArea   MiscVal    MoSold    YrSold  SalePrice  \n",
       "OverallQual      0.064886  0.065166 -0.031406  0.070815 -0.027347   0.790982  \n",
       "YearBuilt       -0.050364  0.004950 -0.034383  0.012398 -0.013618   0.522897  \n",
       "YearRemodAdd    -0.038740  0.005829 -0.010286  0.021490  0.035743   0.507101  \n",
       "TotalBsmtSF      0.084489  0.126053 -0.018479  0.013196 -0.014969   0.613581  \n",
       "1stFlrSF         0.088758  0.131525 -0.021096  0.031372 -0.013604   0.605852  \n",
       "GrLivArea        0.101510  0.170205 -0.002416  0.050240 -0.036526   0.708624  \n",
       "FullBath        -0.008106  0.049604 -0.014290  0.055872 -0.019669   0.560664  \n",
       "TotRmsAbvGrd     0.059383  0.083757  0.024763  0.036907 -0.034516   0.533723  \n",
       "GarageCars       0.050494  0.020934 -0.043080  0.040522 -0.039117   0.640409  \n",
       "GarageArea       0.051412  0.061047 -0.027400  0.027974 -0.027378   0.623431  \n",
       "SalePrice        0.111447  0.092404 -0.021190  0.046432 -0.028923   1.000000  \n",
       "\n",
       "[11 rows x 38 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Corr = train.corr()\n",
    "Corr[Corr['SalePrice']>0.5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\seaborn\\axisgrid.py:2065: UserWarning: The `size` parameter has been renamed to `height`; pleaes update your code.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1260x1260 with 56 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#scatterplot 绘制散点图矩阵注意：多变量作图数据中不能有空值，否则出错\n",
    "sns.set()\n",
    "cols = ['SalePrice', 'OverallQual', 'GrLivArea', 'GarageCars', 'TotalBsmtSF', 'FullBath', 'YearBuilt']\n",
    "sns.pairplot(train[cols], size = 2.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.6 标签分布分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      1460.000000\n",
       "mean     180921.195890\n",
       "std       79442.502883\n",
       "min       34900.000000\n",
       "25%      129975.000000\n",
       "50%      163000.000000\n",
       "75%      214000.000000\n",
       "max      755000.000000\n",
       "Name: SalePrice, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train['SalePrice'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#scipy库中stats对象的.probplot() 方法拟合一个高斯正态分布，以SalePrice为例\n",
    "from scipy.stats import norm\n",
    "from scipy import stats\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "#histogram画直方图,且查看数据是否符合正态分布\n",
    "# 直方图和正态概率图\n",
    "sns.distplot(train['SalePrice'],fit=norm)\n",
    "fig = plt.figure()\n",
    "res = stats.probplot(train['SalePrice'], plot=plt)\n",
    " \n",
    "##  由图像可知，图像的非正态分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skewness: 1.882876\n",
      "Kurtosis: 6.536282\n"
     ]
    }
   ],
   "source": [
    "# 偏度和峰度\n",
    "print(\"Skewness: %f\" % train['SalePrice'].skew())\n",
    "print(\"Kurtosis: %f\" % train['SalePrice'].kurt())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 研究SalePrice和GrLivArea的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 研究SalePrice和GrLivArea的关系\n",
    "data1 = pd.concat([train['SalePrice'], train['GrLivArea']], axis=1)\n",
    "data1.plot.scatter(x='GrLivArea', y='SalePrice', ylim=(0,800000));\n",
    "\n",
    " \n",
    "##  由散点图可知，图像的右下角存在两个异常值，建议去除；图像非正态分布"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 研究SalePrice和TotalBsmtSF的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 研究SalePrice和TotalBsmtSF的关系\n",
    "data1 = pd.concat([train['SalePrice'], train['TotalBsmtSF']], axis=1)\n",
    "data1.plot.scatter(x='TotalBsmtSF', y='SalePrice', ylim=(0,800000));\n",
    " \n",
    "# 直方图和正态概率图，查看是否正态分布\n",
    "fig = plt.figure()\n",
    "sns.distplot(train['TotalBsmtSF'], fit=norm);\n",
    "fig = plt.figure()\n",
    "res = stats.probplot(train['TotalBsmtSF'], plot=plt)\n",
    " \n",
    "##  由散点图可知，图像的右下角存在1个异常值，建议去除该记录；图像非正态分布"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 研究SalePrice和OverallQual的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 研究SalePrice和OverallQual的关系\n",
    "data2 = pd.concat([train['SalePrice'], train['OverallQual']], axis=1)\n",
    "f, ax = plt.subplots(figsize=(8, 6))\n",
    "fig = sns.boxplot(x='OverallQual', y=\"SalePrice\", data=data2)\n",
    "fig.axis(ymin=0, ymax=800000);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.7 查看不同月份的房子的销售量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看不同月份的房子的销售量\n",
    "train.groupby('MoSold')['SalePrice'].count()\n",
    "#一个计数图可以被认为是一个分类直方图，而不是定量的变量。\n",
    "#基本的api和选项与barplot（）相同，因此您可以比较嵌套变量中的计数。\n",
    "#（工作原理就是对输入的数据分类，条形图显示各个分类的数量）具体用法如下：\n",
    "fig,axes=plt.subplots(1,2)\n",
    "sns.countplot(x=\"MoSold\",data=train,ax=axes[0]) #左图\n",
    "sns.countplot(y=\"MoSold\",data=train,ax=axes[1])  #右图\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. 数据质量分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1 缺失值分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>missingNum</th>\n",
       "      <th>missingRatio</th>\n",
       "      <th>existNum</th>\n",
       "      <th>train_notna</th>\n",
       "      <th>test_notna</th>\n",
       "      <th>dtype</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PoolQC</th>\n",
       "      <td>2909</td>\n",
       "      <td>99.657417</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MiscFeature</th>\n",
       "      <td>2814</td>\n",
       "      <td>96.402878</td>\n",
       "      <td>105</td>\n",
       "      <td>54</td>\n",
       "      <td>51</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alley</th>\n",
       "      <td>2721</td>\n",
       "      <td>93.216855</td>\n",
       "      <td>198</td>\n",
       "      <td>91</td>\n",
       "      <td>107</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fence</th>\n",
       "      <td>2348</td>\n",
       "      <td>80.438506</td>\n",
       "      <td>571</td>\n",
       "      <td>281</td>\n",
       "      <td>290</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FireplaceQu</th>\n",
       "      <td>1420</td>\n",
       "      <td>48.646797</td>\n",
       "      <td>1499</td>\n",
       "      <td>770</td>\n",
       "      <td>729</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LotFrontage</th>\n",
       "      <td>486</td>\n",
       "      <td>16.649538</td>\n",
       "      <td>2433</td>\n",
       "      <td>1201</td>\n",
       "      <td>1232</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageCond</th>\n",
       "      <td>159</td>\n",
       "      <td>5.447071</td>\n",
       "      <td>2760</td>\n",
       "      <td>1379</td>\n",
       "      <td>1381</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageFinish</th>\n",
       "      <td>159</td>\n",
       "      <td>5.447071</td>\n",
       "      <td>2760</td>\n",
       "      <td>1379</td>\n",
       "      <td>1381</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageQual</th>\n",
       "      <td>159</td>\n",
       "      <td>5.447071</td>\n",
       "      <td>2760</td>\n",
       "      <td>1379</td>\n",
       "      <td>1381</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <td>159</td>\n",
       "      <td>5.447071</td>\n",
       "      <td>2760</td>\n",
       "      <td>1379</td>\n",
       "      <td>1381</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageType</th>\n",
       "      <td>157</td>\n",
       "      <td>5.378554</td>\n",
       "      <td>2762</td>\n",
       "      <td>1379</td>\n",
       "      <td>1383</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtCond</th>\n",
       "      <td>82</td>\n",
       "      <td>2.809181</td>\n",
       "      <td>2837</td>\n",
       "      <td>1423</td>\n",
       "      <td>1414</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtExposure</th>\n",
       "      <td>82</td>\n",
       "      <td>2.809181</td>\n",
       "      <td>2837</td>\n",
       "      <td>1422</td>\n",
       "      <td>1415</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtQual</th>\n",
       "      <td>81</td>\n",
       "      <td>2.774923</td>\n",
       "      <td>2838</td>\n",
       "      <td>1423</td>\n",
       "      <td>1415</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <td>80</td>\n",
       "      <td>2.740665</td>\n",
       "      <td>2839</td>\n",
       "      <td>1422</td>\n",
       "      <td>1417</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <td>79</td>\n",
       "      <td>2.706406</td>\n",
       "      <td>2840</td>\n",
       "      <td>1423</td>\n",
       "      <td>1417</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MasVnrType</th>\n",
       "      <td>24</td>\n",
       "      <td>0.822199</td>\n",
       "      <td>2895</td>\n",
       "      <td>1452</td>\n",
       "      <td>1443</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MasVnrArea</th>\n",
       "      <td>23</td>\n",
       "      <td>0.787941</td>\n",
       "      <td>2896</td>\n",
       "      <td>1452</td>\n",
       "      <td>1444</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSZoning</th>\n",
       "      <td>4</td>\n",
       "      <td>0.137033</td>\n",
       "      <td>2915</td>\n",
       "      <td>1460</td>\n",
       "      <td>1455</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <td>2</td>\n",
       "      <td>0.068517</td>\n",
       "      <td>2917</td>\n",
       "      <td>1460</td>\n",
       "      <td>1457</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <td>2</td>\n",
       "      <td>0.068517</td>\n",
       "      <td>2917</td>\n",
       "      <td>1460</td>\n",
       "      <td>1457</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Functional</th>\n",
       "      <td>2</td>\n",
       "      <td>0.068517</td>\n",
       "      <td>2917</td>\n",
       "      <td>1460</td>\n",
       "      <td>1457</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utilities</th>\n",
       "      <td>2</td>\n",
       "      <td>0.068517</td>\n",
       "      <td>2917</td>\n",
       "      <td>1460</td>\n",
       "      <td>1457</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Electrical</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1459</td>\n",
       "      <td>1459</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Exterior1st</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Exterior2nd</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageArea</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GarageCars</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KitchenQual</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SaleType</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>object</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <td>1</td>\n",
       "      <td>0.034258</td>\n",
       "      <td>2918</td>\n",
       "      <td>1460</td>\n",
       "      <td>1458</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              missingNum  missingRatio  existNum  train_notna  test_notna  \\\n",
       "index                                                                       \n",
       "PoolQC              2909     99.657417        10            7           3   \n",
       "MiscFeature         2814     96.402878       105           54          51   \n",
       "Alley               2721     93.216855       198           91         107   \n",
       "Fence               2348     80.438506       571          281         290   \n",
       "FireplaceQu         1420     48.646797      1499          770         729   \n",
       "LotFrontage          486     16.649538      2433         1201        1232   \n",
       "GarageCond           159      5.447071      2760         1379        1381   \n",
       "GarageFinish         159      5.447071      2760         1379        1381   \n",
       "GarageQual           159      5.447071      2760         1379        1381   \n",
       "GarageYrBlt          159      5.447071      2760         1379        1381   \n",
       "GarageType           157      5.378554      2762         1379        1383   \n",
       "BsmtCond              82      2.809181      2837         1423        1414   \n",
       "BsmtExposure          82      2.809181      2837         1422        1415   \n",
       "BsmtQual              81      2.774923      2838         1423        1415   \n",
       "BsmtFinType2          80      2.740665      2839         1422        1417   \n",
       "BsmtFinType1          79      2.706406      2840         1423        1417   \n",
       "MasVnrType            24      0.822199      2895         1452        1443   \n",
       "MasVnrArea            23      0.787941      2896         1452        1444   \n",
       "MSZoning               4      0.137033      2915         1460        1455   \n",
       "BsmtFullBath           2      0.068517      2917         1460        1457   \n",
       "BsmtHalfBath           2      0.068517      2917         1460        1457   \n",
       "Functional             2      0.068517      2917         1460        1457   \n",
       "Utilities              2      0.068517      2917         1460        1457   \n",
       "BsmtFinSF1             1      0.034258      2918         1460        1458   \n",
       "BsmtFinSF2             1      0.034258      2918         1460        1458   \n",
       "BsmtUnfSF              1      0.034258      2918         1460        1458   \n",
       "Electrical             1      0.034258      2918         1459        1459   \n",
       "Exterior1st            1      0.034258      2918         1460        1458   \n",
       "Exterior2nd            1      0.034258      2918         1460        1458   \n",
       "GarageArea             1      0.034258      2918         1460        1458   \n",
       "GarageCars             1      0.034258      2918         1460        1458   \n",
       "KitchenQual            1      0.034258      2918         1460        1458   \n",
       "SaleType               1      0.034258      2918         1460        1458   \n",
       "TotalBsmtSF            1      0.034258      2918         1460        1458   \n",
       "\n",
       "                dtype  \n",
       "index                  \n",
       "PoolQC         object  \n",
       "MiscFeature    object  \n",
       "Alley          object  \n",
       "Fence          object  \n",
       "FireplaceQu    object  \n",
       "LotFrontage   float64  \n",
       "GarageCond     object  \n",
       "GarageFinish   object  \n",
       "GarageQual     object  \n",
       "GarageYrBlt   float64  \n",
       "GarageType     object  \n",
       "BsmtCond       object  \n",
       "BsmtExposure   object  \n",
       "BsmtQual       object  \n",
       "BsmtFinType2   object  \n",
       "BsmtFinType1   object  \n",
       "MasVnrType     object  \n",
       "MasVnrArea    float64  \n",
       "MSZoning       object  \n",
       "BsmtFullBath  float64  \n",
       "BsmtHalfBath  float64  \n",
       "Functional     object  \n",
       "Utilities      object  \n",
       "BsmtFinSF1    float64  \n",
       "BsmtFinSF2    float64  \n",
       "BsmtUnfSF     float64  \n",
       "Electrical     object  \n",
       "Exterior1st    object  \n",
       "Exterior2nd    object  \n",
       "GarageArea    float64  \n",
       "GarageCars    float64  \n",
       "KitchenQual    object  \n",
       "SaleType       object  \n",
       "TotalBsmtSF   float64  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看缺失值情况\n",
    "def missing_values(alldata):\n",
    "    alldata_na = pd.DataFrame(alldata.isnull().sum(), columns={'missingNum'})\n",
    "    alldata_na['missingRatio'] = alldata_na['missingNum']/len(alldata)*100\n",
    "    alldata_na['existNum'] = len(alldata) - alldata_na['missingNum']\n",
    "    \n",
    "    alldata_na['train_notna'] = len(train) - train.isnull().sum()\n",
    "    alldata_na['test_notna'] = alldata_na['existNum'] - alldata_na['train_notna'] \n",
    "    alldata_na['dtype'] = alldata.dtypes\n",
    "    \n",
    "    alldata_na = alldata_na[alldata_na['missingNum']>0].reset_index().sort_values(by=['missingNum','index'],ascending=[False,True])\n",
    "    alldata_na.set_index('index',inplace=True)\n",
    "    return alldata_na\n",
    " \n",
    "alldata_na = missing_values(alldata)\n",
    "alldata_na"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2.2 对于pool相关空值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ex    4\n",
      "Gd    4\n",
      "Fa    2\n",
      "Name: PoolQC, dtype: int64\n",
      "\n",
      "不同poolqc的PoolArea的均值 PoolQC\n",
      "Ex    359.75\n",
      "Fa    583.50\n",
      "Gd    648.50\n",
      "Name: PoolArea, dtype: float64\n",
      "\n",
      "查看有PoolArea数据但是没有poolQC的数据      PoolQC  PoolArea\n",
      "2420    NaN       368\n",
      "2503    NaN       444\n",
      "2599    NaN       561\n",
      "\n",
      "查看无PoolArea数据但是有poolQC的数据 Empty DataFrame\n",
      "Columns: [PoolQC, PoolArea]\n",
      "Index: []\n",
      "\n",
      "查看是否有PoolQC不空，PoolArea为空的 Empty DataFrame\n",
      "Columns: [PoolQC, PoolArea]\n",
      "Index: []\n"
     ]
    }
   ],
   "source": [
    "# 查看各个poolQC的分布情况\n",
    "print(alldata['PoolQC'].value_counts())\n",
    "print()\n",
    "# PoolArea的均值\n",
    "poolqc = alldata.groupby('PoolQC')['PoolArea'].mean()\n",
    "print('不同poolqc的PoolArea的均值',poolqc)\n",
    "print()\n",
    "\n",
    "# 查看有PoolArea数据但是没有poolQC的数据\n",
    "poolqcna = alldata[(alldata['PoolQC'].isnull())& (alldata['PoolArea']!=0)][['PoolQC','PoolArea']]\n",
    "print('查看有PoolArea数据但是没有poolQC的数据',poolqcna)\n",
    "print()\n",
    "\n",
    "# 查看无PoolArea数据但是有poolQC的数据\n",
    "poolareana = alldata[(alldata['PoolQC'].notnull()) & (alldata['PoolArea']==0)][['PoolQC','PoolArea']]\n",
    "print('查看无PoolArea数据但是有poolQC的数据',poolareana)\n",
    "print()\n",
    "\n",
    "# 查看是否有'PoolQC'不空，PoolArea为空的\n",
    "print('查看是否有PoolQC不空，PoolArea为空的',alldata[(alldata['PoolQC'].notnull()) & (alldata['PoolArea']==0)][['PoolQC','PoolArea']])\n",
    " \n",
    " \n",
    "# 由结果可知，PoolQC有三种取值，存在3个值QC为空，Area不为空,以PoolQC进行分组，计算PoolArea的均值，最小距离\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2 找出所有Garage前缀的属性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['GarageType' 'GarageYrBlt' 'GarageFinish' 'GarageCars' 'GarageArea'\n",
      " 'GarageQual' 'GarageCond']\n",
      "              missingNum  missingRatio  existNum  train_notna  test_notna  \\\n",
      "index                                                                       \n",
      "GarageType           157      5.378554      2762         1379        1383   \n",
      "GarageYrBlt          159      5.447071      2760         1379        1381   \n",
      "GarageFinish         159      5.447071      2760         1379        1381   \n",
      "GarageCars             1      0.034258      2918         1460        1458   \n",
      "GarageArea             1      0.034258      2918         1460        1458   \n",
      "GarageQual           159      5.447071      2760         1379        1381   \n",
      "GarageCond           159      5.447071      2760         1379        1381   \n",
      "\n",
      "                dtype  \n",
      "index                  \n",
      "GarageType     object  \n",
      "GarageYrBlt   float64  \n",
      "GarageFinish   object  \n",
      "GarageCars    float64  \n",
      "GarageArea    float64  \n",
      "GarageQual     object  \n",
      "GarageCond     object  \n",
      "157\n",
      "0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:7: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "# 找出所有Garage前缀的属性\n",
    "a = pd.Series(alldata.columns)\n",
    "GarageList = a[a.str.contains('Garage')].values\n",
    "print(GarageList)\n",
    " \n",
    "# -step1 GarageYrBlt\t车库建造年份\n",
    "print(alldata_na.ix[GarageList,:])\n",
    "# -step2:检查GarageArea、GarageCars均为0的，其他类别列的空值均填充“none”，数值列填“0”\n",
    "print(len(alldata[(alldata['GarageArea']==0) & (alldata['GarageCars']==0)]))# 157\n",
    "print(len(alldata[(alldata['GarageArea']!=0) & (alldata['GarageCars'].isnull==True)])) # 0\n",
    " \n",
    "# 'GarageYrBlt'到后来与年份一起处理，也有空值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3 找出所有Bsmt前缀的属性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['BsmtQual' 'BsmtCond' 'BsmtExposure' 'BsmtFinType1' 'BsmtFinSF1'\n",
      " 'BsmtFinType2' 'BsmtFinSF2' 'BsmtUnfSF' 'TotalBsmtSF' 'BsmtFullBath'\n",
      " 'BsmtHalfBath']\n",
      "              missingNum  missingRatio  existNum  train_notna  test_notna  \\\n",
      "index                                                                       \n",
      "BsmtQual              81      2.774923      2838         1423        1415   \n",
      "BsmtCond              82      2.809181      2837         1423        1414   \n",
      "BsmtExposure          82      2.809181      2837         1422        1415   \n",
      "BsmtFinType1          79      2.706406      2840         1423        1417   \n",
      "BsmtFinSF1             1      0.034258      2918         1460        1458   \n",
      "BsmtFinType2          80      2.740665      2839         1422        1417   \n",
      "BsmtFinSF2             1      0.034258      2918         1460        1458   \n",
      "BsmtUnfSF              1      0.034258      2918         1460        1458   \n",
      "TotalBsmtSF            1      0.034258      2918         1460        1458   \n",
      "BsmtFullBath           2      0.068517      2917         1460        1457   \n",
      "BsmtHalfBath           2      0.068517      2917         1460        1457   \n",
      "\n",
      "                dtype  \n",
      "index                  \n",
      "BsmtQual       object  \n",
      "BsmtCond       object  \n",
      "BsmtExposure   object  \n",
      "BsmtFinType1   object  \n",
      "BsmtFinSF1    float64  \n",
      "BsmtFinType2   object  \n",
      "BsmtFinSF2    float64  \n",
      "BsmtUnfSF     float64  \n",
      "TotalBsmtSF   float64  \n",
      "BsmtFullBath  float64  \n",
      "BsmtHalfBath  float64  \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  \"\"\"\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>948</th>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1487</th>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1595.0</td>\n",
       "      <td>1595.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2348</th>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>725.0</td>\n",
       "      <td>725.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     BsmtQual BsmtCond BsmtExposure BsmtFinType1  BsmtFinSF1 BsmtFinType2  \\\n",
       "948        Gd       TA          NaN          Unf         0.0          Unf   \n",
       "1487       Gd       TA          NaN          Unf         0.0          Unf   \n",
       "2348       Gd       TA          NaN          Unf         0.0          Unf   \n",
       "\n",
       "      BsmtFinSF2  BsmtUnfSF  TotalBsmtSF  BsmtFullBath  BsmtHalfBath  \n",
       "948          0.0      936.0        936.0           0.0           0.0  \n",
       "1487         0.0     1595.0       1595.0           0.0           0.0  \n",
       "2348         0.0      725.0        725.0           0.0           0.0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 找出所有Bsmt前缀的属性\n",
    "a = pd.Series(alldata.columns)\n",
    "BsmtList = a[a.str.contains('Bsmt')].values\n",
    "print(BsmtList)\n",
    "allBsmtNa = alldata_na.ix[BsmtList,:]\n",
    "print(allBsmtNa)\n",
    "\n",
    "\n",
    "condition = (alldata['BsmtExposure'].isnull()) & (alldata['BsmtCond'].notnull())\n",
    "alldata[condition][BsmtList]\n",
    "\n",
    "# 通过研究发现，BsmtExposure为空时，有三行数据其他值不为空，取众数填充"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Bsmt数据有空值，判断它为空值时其他列的值的情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1265\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>Gd</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mn</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>1044.0</td>\n",
       "      <td>Rec</td>\n",
       "      <td>382.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1426.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2185</th>\n",
       "      <td>TA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>BLQ</td>\n",
       "      <td>1033.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>1127.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2524</th>\n",
       "      <td>TA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Av</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>755.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>995.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     BsmtQual BsmtCond BsmtExposure BsmtFinType1  BsmtFinSF1 BsmtFinType2  \\\n",
       "2040       Gd      NaN           Mn          GLQ      1044.0          Rec   \n",
       "2185       TA      NaN           No          BLQ      1033.0          Unf   \n",
       "2524       TA      NaN           Av          ALQ       755.0          Unf   \n",
       "\n",
       "      BsmtFinSF2  BsmtUnfSF  TotalBsmtSF  BsmtFullBath  BsmtHalfBath  \n",
       "2040       382.0        0.0       1426.0           1.0           0.0  \n",
       "2185         0.0       94.0       1127.0           0.0           1.0  \n",
       "2524         0.0      240.0        995.0           0.0           0.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "condition1 = (alldata['BsmtCond'].isnull()) & (alldata['BsmtExposure'].notnull())\n",
    "print(len(alldata[alldata['BsmtCond']==alldata['BsmtQual']])) \n",
    "alldata[condition1][BsmtList]\n",
    "# 通过研究发现，BsmtCond为空时，有三行数据其他值不为空# 有1265个值的BsmtQual == BsmtCond，所以对应填充"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Fa</td>\n",
       "      <td>No</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>NaN</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     BsmtQual BsmtCond BsmtExposure BsmtFinType1  BsmtFinSF1 BsmtFinType2  \\\n",
       "2217      NaN       Fa           No          Unf         0.0          Unf   \n",
       "2218      NaN       TA           No          Unf         0.0          Unf   \n",
       "\n",
       "      BsmtFinSF2  BsmtUnfSF  TotalBsmtSF  BsmtFullBath  BsmtHalfBath  \n",
       "2217         0.0      173.0        173.0           0.0           0.0  \n",
       "2218         0.0      356.0        356.0           0.0           0.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "condition2 = (alldata['BsmtQual'].isnull()) & (alldata['BsmtExposure'].notnull())\n",
    "alldata[condition2][BsmtList]\n",
    "# 通过研究发现，BsmtQual为空时，有两行数据其他值不为空，填充方法与condition1类似"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0      929\n",
      "24.0      27\n",
      "16.0      14\n",
      "300.0      9\n",
      "288.0      8\n",
      "Name: BsmtFinSF1, dtype: int64\n",
      "0.0      2571\n",
      "294.0       5\n",
      "180.0       5\n",
      "162.0       3\n",
      "539.0       3\n",
      "Name: BsmtFinSF2, dtype: int64\n",
      "0.0    1705\n",
      "1.0    1172\n",
      "2.0      38\n",
      "3.0       2\n",
      "Name: BsmtFullBath, dtype: int64\n",
      "0.0    2742\n",
      "1.0     171\n",
      "2.0       4\n",
      "Name: BsmtHalfBath, dtype: int64\n",
      "Unf    851\n",
      "GLQ    849\n",
      "ALQ    429\n",
      "Rec    288\n",
      "BLQ    269\n",
      "Name: BsmtFinType1, dtype: int64\n",
      "Unf    2493\n",
      "Rec     105\n",
      "LwQ      87\n",
      "BLQ      68\n",
      "ALQ      52\n",
      "Name: BsmtFinType2, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 其他剩下的字段考虑数值型空值填0，标称型空值填none\n",
    "print(alldata['BsmtFinSF1'].value_counts().head(5))# 空值填0\n",
    " \n",
    "print(alldata['BsmtFinSF2'].value_counts().head(5))# 空值填0\n",
    " \n",
    "print(alldata['BsmtFullBath'].value_counts().head(5))# 空值填0\n",
    " \n",
    "print(alldata['BsmtHalfBath'].value_counts().head(5))# 空值填0\n",
    " \n",
    "print(alldata['BsmtFinType1'].value_counts().head(5)) # 空值填众数\n",
    " \n",
    "print(alldata['BsmtFinType2'].value_counts().head(5)) # 空值填众数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.4 MasVnrType\t砖石类型 MasVnrArea\t砖石面积"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MasVnrType    24\n",
      "MasVnrArea    23\n",
      "dtype: int64\n",
      "\n",
      "23\n",
      "1\n",
      "0\n",
      "\n",
      "None       1742\n",
      "BrkFace     879\n",
      "Stone       249\n",
      "BrkCmn       25\n",
      "Name: MasVnrType, dtype: int64\n",
      "\n",
      "MasVnrType\n",
      "BrkCmn     161.0\n",
      "BrkFace    203.0\n",
      "None         0.0\n",
      "Stone      200.0\n",
      "Name: MasVnrArea, dtype: float64\n",
      "\n",
      "     MasVnrType  MasVnrArea\n",
      "2610        NaN       198.0\n"
     ]
    }
   ],
   "source": [
    "print(alldata[['MasVnrType', 'MasVnrArea']].isnull().sum())\n",
    "print()\n",
    "\n",
    "print(len(alldata[(alldata['MasVnrType'].isnull())& (alldata['MasVnrArea'].isnull())])) # 23\n",
    " \n",
    "print(len(alldata[(alldata['MasVnrType'].isnull())& (alldata['MasVnrArea'].notnull())]))\n",
    " \n",
    "print(len(alldata[(alldata['MasVnrType'].notnull())& (alldata['MasVnrArea'].isnull())]))\n",
    "print()\n",
    "\n",
    "print(alldata['MasVnrType'].value_counts())\n",
    "print()\n",
    "\n",
    "MasVnrM = alldata.groupby('MasVnrType')['MasVnrArea'].median()\n",
    "print(MasVnrM)\n",
    "print()\n",
    "mtypena = alldata[(alldata['MasVnrType'].isnull())& (alldata['MasVnrArea'].notnull())][['MasVnrType','MasVnrArea']]\n",
    "print(mtypena)\n",
    "# 由此可知，由一条数据的 MasVnrType 为空而Area不为空，所以，填充方式按照类似poolQC和poolArea的方式，分组填充\n",
    "# 其他数据中MasVnrType空值填fillna(\"None\")，MasVnrArea空值填fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MasVnrType</th>\n",
       "      <th>MasVnrArea</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>624</th>\n",
       "      <td>None</td>\n",
       "      <td>288.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>773</th>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1230</th>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1300</th>\n",
       "      <td>None</td>\n",
       "      <td>344.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1334</th>\n",
       "      <td>None</td>\n",
       "      <td>312.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1669</th>\n",
       "      <td>None</td>\n",
       "      <td>285.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2452</th>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     MasVnrType  MasVnrArea\n",
       "624        None       288.0\n",
       "773        None         1.0\n",
       "1230       None         1.0\n",
       "1300       None       344.0\n",
       "1334       None       312.0\n",
       "1669       None       285.0\n",
       "2452       None         1.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#这部分数据很奇怪，类型为“None\"类型，但是Area却大于0，还有等于1的\n",
    "alldata[(alldata['MasVnrType']=='None')&(alldata['MasVnrArea']!=0)][['MasVnrType','MasVnrArea']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0      1735\n",
       "1.0         3\n",
       "285.0       1\n",
       "312.0       1\n",
       "344.0       1\n",
       "288.0       1\n",
       "Name: MasVnrArea, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#类型为“None\"类型，Area的值的分布\n",
    "alldata[alldata['MasVnrType']=='None']['MasVnrArea'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.5 MS**填充MSSubClass\t住宅类型MSZoning\t分区分类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      MSSubClass MSZoning\n",
      "1915          30      NaN\n",
      "2216          20      NaN\n",
      "2250          70      NaN\n",
      "2904          20      NaN\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>MSZoning</th>\n",
       "      <th>C (all)</th>\n",
       "      <th>FV</th>\n",
       "      <th>RH</th>\n",
       "      <th>RL</th>\n",
       "      <th>RM</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSSubClass</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>3</td>\n",
       "      <td>34</td>\n",
       "      <td>4</td>\n",
       "      <td>1016</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>61</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>159</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>529</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>57</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>115</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>92</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>117</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>31</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "MSZoning    C (all)  FV  RH    RL   RM\n",
       "MSSubClass                            \n",
       "20                3  34   4  1016   20\n",
       "30                8   0   2    61   67\n",
       "40                0   0   0     4    2\n",
       "45                0   0   1     6   11\n",
       "50                7   0   2   159  119\n",
       "60                0  43   0   529    3\n",
       "70                4   0   3    57   63\n",
       "75                0   0   0     9   14\n",
       "80                0   0   0   115    3\n",
       "85                0   0   0    47    1\n",
       "90                0   0   4    92   13\n",
       "120               0  19   6   117   40\n",
       "150               0   0   0     1    0\n",
       "160               0  43   0    21   64\n",
       "180               0   0   0     0   17\n",
       "190               3   0   4    31   23"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(alldata[alldata['MSSubClass'].isnull() | alldata['MSZoning'].isnull()][['MSSubClass','MSZoning']])\n",
    "pd.crosstab(alldata.MSSubClass, alldata.MSZoning)#交叉表\n",
    "#通过观察30/70 'RM'和20'RL'的组合较多。对应填充"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.6 LotFrontage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LotFrontage     486\n",
      "Neighborhood      0\n",
      "dtype: int64\n",
      "60.0    276\n",
      "80.0    137\n",
      "70.0    133\n",
      "50.0    117\n",
      "75.0    105\n",
      "Name: LotFrontage, dtype: int64\n",
      "\n",
      "NAmes      443\n",
      "CollgCr    267\n",
      "OldTown    239\n",
      "Edwards    194\n",
      "Somerst    182\n",
      "NridgHt    166\n",
      "Gilbert    165\n",
      "Sawyer     151\n",
      "NWAmes     131\n",
      "SawyerW    125\n",
      "Mitchel    114\n",
      "BrkSide    108\n",
      "Crawfor    103\n",
      "IDOTRR      93\n",
      "Timber      72\n",
      "NoRidge     71\n",
      "StoneBr     51\n",
      "SWISU       48\n",
      "ClearCr     44\n",
      "MeadowV     37\n",
      "BrDale      30\n",
      "Blmngtn     28\n",
      "Veenker     24\n",
      "NPkVill     23\n",
      "Blueste     10\n",
      "Name: Neighborhood, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#考虑到LotFrontage\t与街道连接的线性脚与Neighborhood\t房屋附近位置 存在一定的关系\n",
    " \n",
    "print(alldata[[\"LotFrontage\", \"Neighborhood\"]].isnull().sum())\n",
    "print(alldata[\"LotFrontage\"].value_counts().head(5)) \n",
    "print()\n",
    "print(alldata[\"Neighborhood\"].value_counts())\n",
    "# 考虑通过一定的方式来填充\n",
    "# 例如：\n",
    "alldata[\"LotFrontage\"] = alldata.groupby(\"Neighborhood\")[\"LotFrontage\"].transform(\n",
    "    lambda x: x.fillna(x.median()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.7 其他列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Functional        2\n",
      "Utilities         2\n",
      "SaleType          1\n",
      "Electrical        1\n",
      "FireplaceQu    1420\n",
      "Alley          2721\n",
      "Fence          2348\n",
      "MiscFeature    2814\n",
      "KitchenQual       1\n",
      "LotFrontage       0\n",
      "Exterior1st       1\n",
      "Exterior2nd       1\n",
      "dtype: int64\n",
      "\n",
      "Typ     2717\n",
      "Min2      70\n",
      "Min1      65\n",
      "Mod       35\n",
      "Maj1      19\n",
      "Name: Functional, dtype: int64\n",
      "AllPub    2916\n",
      "NoSeWa       1\n",
      "Name: Utilities, dtype: int64\n",
      "WD       2525\n",
      "New       239\n",
      "COD        87\n",
      "ConLD      26\n",
      "CWD        12\n",
      "Name: SaleType, dtype: int64\n",
      "SBrkr    2671\n",
      "FuseA     188\n",
      "FuseF      50\n",
      "FuseP       8\n",
      "Mix         1\n",
      "Name: Electrical, dtype: int64\n",
      "MnPrv    329\n",
      "GdPrv    118\n",
      "GdWo     112\n",
      "MnWw      12\n",
      "Name: Fence, dtype: int64\n",
      "Shed    95\n",
      "Gar2     5\n",
      "Othr     4\n",
      "TenC     1\n",
      "Name: MiscFeature, dtype: int64\n",
      "TA    1492\n",
      "Gd    1151\n",
      "Ex     205\n",
      "Fa      70\n",
      "Name: KitchenQual, dtype: int64\n",
      "VinylSd    1025\n",
      "MetalSd     450\n",
      "HdBoard     442\n",
      "Wd Sdng     411\n",
      "Plywood     221\n",
      "Name: Exterior1st, dtype: int64\n",
      "VinylSd    1014\n",
      "MetalSd     447\n",
      "HdBoard     406\n",
      "Wd Sdng     391\n",
      "Plywood     270\n",
      "Name: Exterior2nd, dtype: int64\n",
      "Gd    744\n",
      "TA    592\n",
      "Fa     74\n",
      "Po     46\n",
      "Ex     43\n",
      "Name: FireplaceQu, dtype: int64\n",
      "Grvl    120\n",
      "Pave     78\n",
      "Name: Alley, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "others = ['Functional','Utilities','SaleType','Electrical', \"FireplaceQu\",'Alley',\"Fence\", \"MiscFeature\",\\\n",
    "          'KitchenQual',\"LotFrontage\",'Exterior1st','Exterior2nd']\n",
    "print(alldata[others].isnull().sum())\n",
    "print()\n",
    "print(alldata['Functional'].value_counts().head(5)) # 填众数\n",
    "print(alldata['Utilities'].value_counts().head(5)) # 填众数\n",
    "print(alldata['SaleType'].value_counts().head(5)) # 填众数\n",
    "print(alldata['Electrical'].value_counts().head(5)) # 填众数\n",
    "print(alldata[\"Fence\"].value_counts()) # 填众数\n",
    "print(alldata[\"MiscFeature\"].value_counts().head(5)) # 填众数\n",
    "print(alldata['KitchenQual'].value_counts().head(5)) # 填众数\n",
    "print(alldata['Exterior1st'].value_counts().head(5)) # 填众数\n",
    "print(alldata['Exterior2nd'].value_counts().head(5)) # 填众数\n",
    "print(alldata['FireplaceQu'].value_counts().head(5)) # 填'none'\n",
    "print(alldata['Alley'].value_counts().head(5)) # 填'none'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>...</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2713</th>\n",
       "      <td>160</td>\n",
       "      <td>FV</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2544</td>\n",
       "      <td>Pave</td>\n",
       "      <td>Pave</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2865</th>\n",
       "      <td>160</td>\n",
       "      <td>RM</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2522</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 79 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "2713         160       FV         24.0     2544   Pave  Pave      Reg   \n",
       "2865         160       RM         24.0     2522   Pave   NaN      Reg   \n",
       "\n",
       "     LandContour Utilities LotConfig  ... ScreenPorch PoolArea PoolQC Fence  \\\n",
       "2713         Lvl    AllPub    Inside  ...           0        0    NaN   NaN   \n",
       "2865         Lvl    AllPub    Inside  ...           0        0    NaN   NaN   \n",
       "\n",
       "     MiscFeature MiscVal  MoSold  YrSold  SaleType  SaleCondition  \n",
       "2713         NaN       0       7    2006        WD         Normal  \n",
       "2865         NaN       0       5    2006        WD         Normal  \n",
       "\n",
       "[2 rows x 79 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alldata[alldata[alldata.columns].duplicated()==True]# 但是考虑到当前重复值后来不影响应用 所以可以不用删除"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. 数据预处理\n",
    "\n",
    "## 3.1 数据清洗"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1.1 缺失值处理\n",
    "- 对于pool相关空值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     PoolQC  PoolArea\n",
      "2420    NaN       368\n",
      "2503    NaN       444\n",
      "2599    NaN       561\n",
      "PoolQC\n",
      "Ex    359.75\n",
      "Fa    583.50\n",
      "Gd    648.50\n",
      "Name: PoolArea, dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "<class 'pandas.core.series.Series'>\n",
      "<class 'pandas.core.series.Series'>\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:8: FutureWarning: \n",
      "The current behaviour of 'Series.argmin' is deprecated, use 'idxmin'\n",
      "instead.\n",
      "The behavior of 'argmin' will be corrected to return the positional\n",
      "minimum in the future. For now, use 'series.values.argmin' or\n",
      "'np.argmin(np.array(values))' to get the position of the minimum\n",
      "row.\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "poolqcna = alldata[(alldata['PoolQC'].isnull())& (alldata['PoolArea']!=0)][['PoolQC','PoolArea']]\n",
    "print(poolqcna)\n",
    "areamean = alldata.groupby('PoolQC')['PoolArea'].mean()\n",
    "print(areamean)\n",
    "for i in poolqcna.index:\n",
    "    v = alldata.loc[i,['PoolArea']].values\n",
    "    print(type(np.abs(v-areamean)))\n",
    "    alldata.loc[i,['PoolQC']] = np.abs(v-areamean).astype('float64').argmin()\n",
    "    \n",
    "alldata['PoolQC'] = alldata[\"PoolQC\"].fillna(\"None\")\n",
    "alldata['PoolArea'] = alldata[\"PoolArea\"].fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 对于Garage*相关空值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "alldata[['GarageCond','GarageFinish','GarageQual','GarageType']] = alldata[['GarageCond','GarageFinish','GarageQual','GarageType']].fillna('None')\n",
    "alldata[['GarageCars','GarageArea']] = alldata[['GarageCars','GarageArea']].fillna(0)\n",
    "alldata['Electrical'] = alldata['Electrical'].fillna( alldata['Electrical'].mode()[0])#众数，频数最高\n",
    " \n",
    "# 注意此处'GarageYrBlt'尚未填充"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 对于Bsmt*相关空值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:6: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  \n",
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:9: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  if __name__ == '__main__':\n",
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:12: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  if sys.path[0] == '':\n",
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:16: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  app.launch_new_instance()\n",
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:18: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n"
     ]
    }
   ],
   "source": [
    "a = pd.Series(alldata.columns)\n",
    "#print(a)\n",
    "BsmtList = a[a.str.contains('Bsmt')].values\n",
    " \n",
    "condition = (alldata['BsmtExposure'].isnull()) & (alldata['BsmtCond'].notnull()) # 3个 ##True Flase\n",
    "alldata.ix[(condition),'BsmtExposure'] = alldata['BsmtExposure'].mode()[0]  #BsmtExposure取众数\n",
    " \n",
    "condition1 = (alldata['BsmtCond'].isnull()) & (alldata['BsmtExposure'].notnull()) # 3个\n",
    "alldata.ix[(condition1),'BsmtCond'] = alldata.ix[(condition1),'BsmtQual']\n",
    " \n",
    "condition2 = (alldata['BsmtQual'].isnull()) & (alldata['BsmtExposure'].notnull()) # 2个\n",
    "alldata.ix[(condition2),'BsmtQual'] = alldata.ix[(condition2),'BsmtCond']\n",
    " \n",
    "# 对于BsmtFinType1和BsmtFinType2\n",
    "condition3 = (alldata['BsmtFinType1'].notnull()) & (alldata['BsmtFinType2'].isnull())\n",
    "alldata.ix[condition3,'BsmtFinType2'] = 'Unf'\n",
    " \n",
    "allBsmtNa = alldata_na.ix[BsmtList,:]\n",
    "allBsmtNa_obj = allBsmtNa[allBsmtNa['dtype']=='object'].index\n",
    "allBsmtNa_flo = allBsmtNa[allBsmtNa['dtype']!='object'].index\n",
    "alldata[allBsmtNa_obj] =alldata[allBsmtNa_obj].fillna('None')\n",
    "alldata[allBsmtNa_flo] = alldata[allBsmtNa_flo].fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- MasVnr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: FutureWarning: \n",
      "The current behaviour of 'Series.argmin' is deprecated, use 'idxmin'\n",
      "instead.\n",
      "The behavior of 'argmin' will be corrected to return the positional\n",
      "minimum in the future. For now, use 'series.values.argmin' or\n",
      "'np.argmin(np.array(values))' to get the position of the minimum\n",
      "row.\n",
      "  \"\"\"\n"
     ]
    }
   ],
   "source": [
    "MasVnrM = alldata.groupby('MasVnrType')['MasVnrArea'].median() #中位数\n",
    "mtypena = alldata[(alldata['MasVnrType'].isnull())& (alldata['MasVnrArea'].notnull())][['MasVnrType','MasVnrArea']]\n",
    "for i in mtypena.index:\n",
    "    v = alldata.loc[i,['MasVnrArea']].values\n",
    "    alldata.loc[i,['MasVnrType']] = np.abs(v-MasVnrM).astype('float64').argmin()\n",
    "    \n",
    "alldata['MasVnrType'] = alldata[\"MasVnrType\"].fillna(\"None\")\n",
    "alldata['MasVnrArea'] = alldata[\"MasVnrArea\"].fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- MS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "alldata[\"MSZoning\"] = alldata.groupby(\"MSSubClass\")[\"MSZoning\"].transform(lambda x: x.fillna(x.mode()[0]))\n",
    "#print(alldata[\"MSZoning\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- LotFrontage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用多项式拟合填充\n",
    " \n",
    "x = alldata.loc[alldata[\"LotFrontage\"].notnull(), \"LotArea\"]\n",
    "y = alldata.loc[alldata[\"LotFrontage\"].notnull(), \"LotFrontage\"]\n",
    "t = (x <= 25000) & (y <= 150)\n",
    "p = np.polyfit(x[t], y[t], 1)\n",
    "alldata.loc[alldata['LotFrontage'].isnull(), 'LotFrontage'] = \\\n",
    "np.polyval(p, alldata.loc[alldata['LotFrontage'].isnull(), 'LotArea'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 其他"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "alldata['KitchenQual'] = alldata['KitchenQual'].fillna(alldata['KitchenQual'].mode()[0]) # 用众数填充\n",
    "alldata['Exterior1st'] = alldata['Exterior1st'].fillna(alldata['Exterior1st'].mode()[0])\n",
    "alldata['Exterior2nd'] = alldata['Exterior2nd'].fillna(alldata['Exterior2nd'].mode()[0])\n",
    "alldata[\"Functional\"] = alldata[\"Functional\"].fillna(alldata['Functional'].mode()[0])\n",
    "alldata[\"SaleType\"] = alldata[\"SaleType\"].fillna(alldata['SaleType'].mode()[0])\n",
    "alldata[\"Utilities\"] = alldata[\"Utilities\"].fillna(alldata['Utilities'].mode()[0])\n",
    " \n",
    "alldata[[\"Fence\", \"MiscFeature\"]] = alldata[[\"Fence\", \"MiscFeature\"]].fillna('None')\n",
    "alldata['FireplaceQu'] = alldata['FireplaceQu'].fillna('None')\n",
    "alldata['Alley'] = alldata['Alley'].fillna('None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GarageYrBlt    159\n",
      "dtype: int64\n",
      "MSSubClass       0\n",
      "MSZoning         0\n",
      "LotFrontage      0\n",
      "LotArea          0\n",
      "Street           0\n",
      "Alley            0\n",
      "LotShape         0\n",
      "LandContour      0\n",
      "Utilities        0\n",
      "LotConfig        0\n",
      "LandSlope        0\n",
      "Neighborhood     0\n",
      "Condition1       0\n",
      "Condition2       0\n",
      "BldgType         0\n",
      "HouseStyle       0\n",
      "OverallQual      0\n",
      "OverallCond      0\n",
      "YearBuilt        0\n",
      "YearRemodAdd     0\n",
      "RoofStyle        0\n",
      "RoofMatl         0\n",
      "Exterior1st      0\n",
      "Exterior2nd      0\n",
      "MasVnrType       0\n",
      "MasVnrArea       0\n",
      "ExterQual        0\n",
      "ExterCond        0\n",
      "Foundation       0\n",
      "BsmtQual         0\n",
      "                ..\n",
      "HalfBath         0\n",
      "BedroomAbvGr     0\n",
      "KitchenAbvGr     0\n",
      "KitchenQual      0\n",
      "TotRmsAbvGrd     0\n",
      "Functional       0\n",
      "Fireplaces       0\n",
      "FireplaceQu      0\n",
      "GarageType       0\n",
      "GarageYrBlt      0\n",
      "GarageFinish     0\n",
      "GarageCars       0\n",
      "GarageArea       0\n",
      "GarageQual       0\n",
      "GarageCond       0\n",
      "PavedDrive       0\n",
      "WoodDeckSF       0\n",
      "OpenPorchSF      0\n",
      "EnclosedPorch    0\n",
      "3SsnPorch        0\n",
      "ScreenPorch      0\n",
      "PoolArea         0\n",
      "PoolQC           0\n",
      "Fence            0\n",
      "MiscFeature      0\n",
      "MiscVal          0\n",
      "MoSold           0\n",
      "YrSold           0\n",
      "SaleType         0\n",
      "SaleCondition    0\n",
      "Length: 79, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(alldata.isnull().sum()[alldata.isnull().sum()>0])\n",
    "#至此， 还有一个属性未填充 # GarageYrBlt    159\n",
    "\n",
    "year_map = pd.concat(pd.Series('YearGroup' + str(i+1), index=range(1871+i*20,1891+i*20)) for i in range(0, 7))\n",
    "# 将年份对应映射\n",
    "alldata.GarageYrBlt = alldata.GarageYrBlt.map(year_map)\n",
    "alldata['GarageYrBlt']= alldata['GarageYrBlt'].fillna('None')# 必须 离散化之后再对应映射\n",
    "print(alldata.isnull().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2 异常值处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Int64Index([523, 1298], dtype='int64')\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(train.GrLivArea,train.SalePrice)\n",
    "plt.show()\n",
    " \n",
    "# # 删除掉异常值GrLivArea>4000但是销售价格低于200000的记录\n",
    "outliers_id = train[(train.GrLivArea>4000) & (train.SalePrice<200000)].index\n",
    "print(outliers_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2919\n",
      "2917\n",
      "1460\n",
      "(1458,)\n"
     ]
    }
   ],
   "source": [
    "# 删除掉异常值\n",
    "print(len(alldata))\n",
    "alldata = alldata.drop(outliers_id)\n",
    "print(len(alldata))\n",
    "print(len(train))\n",
    "Y=train.SalePrice.drop(train[(train.GrLivArea>4000) & (train.SalePrice<200000)].index)\n",
    "print(Y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter(train.GrLivArea,train.SalePrice)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1458, 80)\n"
     ]
    }
   ],
   "source": [
    "#保存数据清洗后的数据，为接下来的操作准备数据集\n",
    "train_now = pd.concat([alldata.iloc[:1458,:],Y], axis=1)#行对齐，然后将不同列名称的两张表合并\n",
    "print(train_now.shape)\n",
    "test_now = alldata.iloc[1458:,:]\n",
    "train_now.to_csv('./clean_data/train_afterclean.csv')\n",
    "test_now.to_csv('./clean_data/test_afterclean.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
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